Gaming with Science

#Wingspan #ElizabethHargrave #Interview #Designer #BoardGames #Science
Summary
After 3 years of  comparing every game to Wingspan, we finally get to talk with the designer herself, Elizabeht Hargrave! We talk about her design process, favorite games and memories as a designer, current and future projects, and all sort of other fun stuff. And about birds, of course. (And butterflies, foxes, seashells, and other wonderful things.) So if you, like us, have been waiting years for this moment, please pull up a chair and enjoy this special bonus episode of Gaming with Science! 
Timestamps
00:00 Introductions
01:42 Wingpan and spinoffs
08:23 Game inspirations
18:08 Thoughts as a game designer
26:12 Inclusivity, gaming, and science
32:14 Parting advice and favorite games
Links
Elizabeth Hargrave (official website)
Unpub.org
The Strong Museum of Play
The Fox Experiment (New York Times)
Flight Behavior by Barbara Kingsolver (Wikipedia)
Monarchs are not avoiding an ancient mountain (Michigan Enjoyer)
Monarch butterfly migration (Wikipedia)
Argan oil from goat poop (CBS news)
Ambergris from sperm whale intestines (Wikipedia) 
Portrait photo by Matt Cohen; background photo by JunBo Sun/Unsplash
Find our socials at https://www.gamingwithscience.net 
This episode of Gaming with Science™ was produced with the help of the University of Georgia and is distributed under a Creative Commons Attribution-Noncommercial (CC BY-NC 4.0) license.
Full Transcript
(Some platforms truncate the transcript due to length restrictions. If so, you can always find the full transcript on https://www.gamingwithscience.net/ )
Brian  0:06  Hello and welcome to the Gaming with Science podcast, where we talk about the science behind some of your favorite games.
Jason Wallace  0:11  In today's episode, we're going to be interviewing Elizabeth Hargrave. All right, everyone, welcome back to Game with Science. This is Jason.
Brian  0:19  This is Brian,
Jason Wallace  0:20  and today we are joined by a very special interview guest, possibly one of the people we've wanted to have on here for the longest time since basically day one of the podcast, Elizabeth Hargrave, who you may recognize from some titles we've done on here, like Wingspan and Undergrove, and most recently the Fox Experiment. So, Elizabeth, for people who haven't already figured out who you are from listening to prior episodes. Could you give us a quick introduction about who you are and how you got into game design?
Elizabeth  0:46  Yeah, my name's Elizabeth. I designed all those games and some others too.
Brian  0:51  Mariposas is on our list. Don't worry.
Elizabeth  0:54  Fantastic. I'll try and stay ahead of you guys.
Brian  1:01  Appreciate that. Thank you.
Elizabeth  1:02  I am doing game design full time. I started back in 2013. Wingspan was the first thing I worked on. It looked nothing like Wingspan when I started on it. I mean, it had birds, but I didn't know what I was doing, and it evolved a lot over time. And now here I am.
Jason Wallace  1:20  If I remember right, you were doing policy work before that, weren't you?
Elizabeth  1:24  Yeah, I had a decently long career as a health policy analyst. I live outside of Washington D.C. and I came here to work for the federal government many, many years ago.
Jason Wallace  1:35  Well, that is a hard switch, but we are all very grateful for your contributions to the board game community. I actually have a question there about Wingspan itself. So it was your first game, and it's an amazing game, but it sounds like it was a long and torturous road to get there. You say it looked nothing like it does now from originally. How many different iterations did it go through? My original question was, how did your first game become so good? And it sounds like the answer is a whole lot of work. Like, what was that work?
Elizabeth  2:02  Yeah, and it was iteration, and I did not count. My first cards for Wingspan were literally like written in pencil on cardstock, and I play tested it a lot with just friends and family for a while. Eventually, I got hooked up with a playtesting convention up in Baltimore called Unpub.
Brian  2:24  Oh yeah, I know Unpub.
Elizabeth  2:25  for unpublished games. Which is awesome for anyone on the East Coast. Really, people come from all over now. If you're anywhere near the Baltimore area in the spring, you can just go and play test people's games all weekend. It's amazing. Anyway, I got hooked up with that, and through that, sort of started meeting more designers in the DC area. Started play testing more regularly with people who are thinking harder about games instead of just my friends, which makes a difference. And sort of settled into a regular weekly play testing pattern with some other designers here in the D.C. area, which definitely started to move me forward more quickly.
Brian  3:08  Do you still have some of those original pencil-on index cards, cards kicking around somewhere?
Elizabeth  3:13  I took a picture of some of them and I gave a bunch of my stuff to the Strong Museum of Play in Rochester, New York.
Brian  3:21  The Strong Museum of play. We're gonna have to drop that in the show notes for sure.
Jason Wallace  3:26  I think that's a field trip, Brian.
Brian  3:27  Yeah, for sure to make a field
Elizabeth  3:29  trip.
Brian  3:29  Cool.
Jason Wallace  3:30  So we love games, but on this podcast especially, we love games that we call hard science games. So the games that are not only fun to play, but that include a very strong like real-world scientific component, and it's become the joke that we practically can't get through an episode without mentioning Wingspan as being the poster child of what does this really well because it's a very fun game, but there's so much of real-world science and biology reflected in it-not just the good illustrations, but like the nest types, or the number of eggs, or the distribution maps, or genus and species names. Now, some of these I know have mechanical components to them, and they make sense, like the different types of nests, the egg sizes. Those are resources in the game you can use to get points. Some of them, though, are, for lack of a better word, decorative things like putting the genus species name on there, the little maps that show their range. And I guess my question is, what inspired you to put that many layers of actual ornithology, actual birding information on these cards? And at any point, did you get pushback from people, from your play testers or from your publisher about things that are on the cards that don't actually have to do with the mechanics of the game?
Brian  4:38  Did they want you to strip out the unnecessary bits?
Elizabeth  4:41  I don't think I ever got pushback. No, I think, Jamey Stegmaier, owner of Stonemaier games, co-owner. When I pitched Wingspan to him, I remember him having this moment that was like, I remember sitting down as a kid with my grandma's bird field guides.
Brian  4:59  Awesome.
Elizabeth  5:00  He had like this core memory, and I think that's part of the resonance of Wingspan for a lot of people. They have some experience with birds that goes way back, but for him, it was field guides specifically that my prototype made him think of, which was sort of intentional. But I think because we both sort of had that touch point for how we interact with bird information, then it makes sense that the genus name is there, that the range map is there. They're like the things that you see in a field guide of birds, and it makes each card feel sort of like a page in a field guide.
Brian  5:37  The illustrations are fantastic.
Elizabeth  5:39  I can't take any credit for that. Just to be clear, because I had someone the other day reach out to me for a pet portrait. Oh no, that is not my part of the game.
Jason Wallace  5:51  And so there's also been several spinoff games. First, Wyrmspan, which being about dragons, will never show up on this podcast, and then Finspan, which we actually did do an episode on, and we got to talk to Brynn Devine, who was the scientific consultant involved in that. How much have you been involved in that? Are you more of an executive producer role? Because I noticed when I was looking up your gameography, I didn't see those actually listed under your name. So is that you take more of a I don't know what to call it, like
Elizabeth  6:16  yeah, like a consultant kind of. So Wyrmspan came first, like you said, and , who designed that, lives here in the D.C. area. We play test with each other every week now. So when she started working on Wyrmspan, she already had Apiary with Stonemaier games. I don't think it had come out yet, but that's how Jamie knew her and wanted, you know, had thought of her to work on Wyrmspan, and I thought that was a great idea. He offered it to me, but I did not have any interest in working with dragons, and I was busy on other stuff. So I sort of helped get Connie going in the sense that I set her down with my spreadsheet of how I think about structuring wingspan cards in terms of what are the moving pieces of how to do the score versus the powers versus the requirements and things like that. We play tested it along the way and had a lot of very interesting conversations about like what makes something feel like it's in a family with wingspan but its own thing. And it went a little bit too far in both directions on on that in terms of like so far away that it didn't feel like a wingspan game, and then so close that you know we wanted to differentiate a little bit more. So that was a super interesting process to me. But Connie was doing all the hands-on, like designing every card, designing how it works, all of that stuff. And then similar with finspan, although that was second and sort of even learned a little bit from that wyrmspan experience by the time it got going. And then at some point, I had my own prototype of fin span that I had made, and I got to go play it with a marine biologist that I knew. I participated in that part of it too, in terms of the scientific checking.
Brian  7:59  So obviously, wingspan sort of the theme is very obvious, and at least from we we understand from your biography is like a personal connection. But then looking at these other three games, and I'm sorry if I'm missing one: Mariposis, Undergrove, and The Fox Experiment are the three that I'm thinking of. Is there what I'm missing?
Elizabeth  8:14  Well, I have Tussie Mussie, which is not really science based.
Brian  8:17  Okay, which I'm sure is very fun, but again,
Elizabeth  8:20  yeah, and now I have Sanibel, which is about seashells.
Brian  8:23  Oh, that's a so what I was going to say is like the Mariposas, the Fox Experiment, and Undergrove. They're like these very inspirational scientific stories. There's a narrative there. How do you get inspired to choose what topic you want to make a game about?
Elizabeth  8:39  I have at this point, a very long running list on my phone of like, oh, this would make this seems like you could do a game about it. This would be an interesting, or like this is a fascinating thing, or this is a cool piece of art, even or funky animal or whatever. But the thing that really gets me to start working on something is having a flash of inspiration that is okay. Here's this cool thing in the world, but this is how you would actually express that in a game mechanic.
Brian  9:11  Gotcha. That's like finding the fun of like, what is the metaphor of this going to be? How are we going to abstract this?
Elizabeth  9:16  Yeah, I
Brian  9:17  was just thinking how each of those fox experiment, undergrowth, mariposas, each of those, I think, have been covers of National Geographic at some point or the other in terms of the story.
Elizabeth  9:28  That's interesting. Yeah, for Wingspin, it was really like let's do a tableau builder where you just get to like have your birds laid out in front of you. And the fox experiment was, you know, the idea of the genetics of these foxes and like such an interesting story of the selective breeding and like obviously for genetics I wanted there to be like dice rolling and some way to pass genes down through generations and so the piece that like my brain latched onto was like how can I create. Information getting passed through generations for that game, and so that's like the core little spark of inspiration that the whole thing then spiraled out from there.
Brian  10:09  Plus, you get to name your fox pups.
Elizabeth  10:11  Yes, which was in and out depending on how we were going to do the actual component of tracking the information, right? Like it wasn't always dry erase. At some points, it was little cardboard chits, and you couldn't write on them. And part of the reason the dry erase won because people like get so much pleasure out of names of foxes. Like really, an unexpected bonus of that game, for sure.
Jason Wallace  10:36  Yes, although we did the boring ones. Oh, this is F 123.
Brian  10:40  That was fun for us. No, we did. It was fun for us. Well, eventually, Jason did start giving him names, but like we liked. Oh, because you wanted because we're big dorks where they
Elizabeth  10:48  like actually fit in the family.
Brian  10:49  Kinda, yeah.
Elizabeth  10:51  Yeah, we did a little bit of that in the actual experiment. Apparently, by keeping the first letter consistent.
Brian  10:58  Oh, interesting. Parents
Elizabeth  11:00  to offspring.
Brian  11:01  Okay,
Elizabeth  11:02  I think from the mom, they passed down the first letter of the mom's name.
Brian  11:05  Very nice. They must have gone through a lot of variations of those names then.
Elizabeth  11:08  I'm sure they also had a numbering system. But it was I read that the foxes have names.
Brian  11:15  Cool.
Jason Wallace  11:16  And I guess one question I have is, how did you hear about these things? Like, okay, lots of people are into birds, but like the fox experiment is a fairly obscure like animal evolution thing, and then mycelial networks for undergrowth. These are not things that most people run across. Like, how do you run across these particular things? Was it National Geographic or
Elizabeth  11:38  I don't think because the National Geographic article, I think, was too long ago for it to have been that. I don't remember how I heard about the Fox experiment. It might have been Radiolab.
Brian  11:47  Oh, that makes sense.
Elizabeth  11:48  There was  also a New York Times article about it at one point. I don't remember which was the first, but like it was multiple things that I heard about it, and it's just such a great story. What was the other?
Brian  12:00  So there's Mariposas about the monarch migration
Jason Wallace  12:03  and Undergrove.
Elizabeth  12:04  So for Undergrove, I am a mushroom collector, a member and past president of the Mycological Association of Washington D.C. Oh, that's great! I'm just a mushroom geek. Like I know mycelia, I know lots of mushrooms.
Brian  12:18  So I am in the Department of Plant Pathology. So I am surrounded by mycologists, although I am not one myself.
Elizabeth  12:25  And you know, Mariposas, which is about migrating monarch butterflies. One of the ways that I heard about that was Barbara Kingsolver has a novel called Flight Behavior. No, but I read that after. So okay, maybe it was just a guidebook for Mexico because I went to one of the monarch sanctuaries in Mexico.
Brian  12:45  That's cool.
Elizabeth  12:45  Way back in the early 2000s, and then several years later, I read Barbara Kingsolver's book *Flight Behavior* and my brain started going about this should be a game where you're actually moving the monarch butterflies on the map
Brian  12:59  from place to place. Is it the monarch butterfly where they still have this pattern in their migration, where they like take this weird loop, and the assumption is that there used to be an obstacle there, and the obstacle is not there anymore?
Elizabeth  13:09  I am not aware of that, but that would be amazing.
Brian  13:12  I'll double check to see if that's true. I'm pretty sure that's the monarch.
Jason Wallace  13:16  Hey there, this is editor Jason from the Future. Just with a quick update here, we looked this up afterwards, and it turns out that while monarchs do veer east on their migration back up towards the northern part of the United States and Canada, it is not due to some missing mountain. The monarch migration is probably only at most 10,000 years old because all of Canada was covered by glaciers at that point, which is not really great monarch habitat. And some sources even think that the migration may only be a few centuries old and might even have been triggered by deforestation once Europeans came over and started clearing forests for farmland. Short answer is that people don't seem to actually know what causes it. We'll link some sources in the show notes so you can look up more if you want. And with that, we'll head back to the show.
Elizabeth  13:53  There's a few other migratory species of butterfly, which is just-it's wild. They're such tiny little creatures to go so far.
Jason Wallace  14:00  You wonder how they have the energy to do that.
Brian  14:03  I mean, they they don't, right? They die halfway, and it's a multi generational,
Elizabeth  14:08  which is even more mind blowing.
Jason Wallace  14:09  True, true. Now you just said you've got a phone full of ideas of possible themes. Is there any theme that you've just had forever and you just can't figure out how to make it stick. He's like, "Oh, if only I could make something about paramecia, that would be  I would have reached apotheosis. Like, is there anything like that? Just nags that you've never managed to figure it out,
Brian  14:32  or like you pick up off the shelf and you put it down, and you pick it up and you put it down.
Elizabeth  14:36  Yeah, I kind of work on things one at a time, so it's like I start working on something, and I bang it into submission. Yeah, I have a lot of things on my list. I'm just looking at my unfinished prototypes that I have set aside. I would love to do a game about the fact that argan, like argan oil, you know, that's used in lots of cosmetics. Is harvested by these goats that climb up in the trees and eat the fruits of the trees, and then poop out the seeds. And people collect the seeds out of the goat poop.
Brian  15:13  That's I'm aware of civet coffee. I'll be honest. I've never heard of argan oil. That's that's crazy.
Brian  15:21  That's like the weird, like red pigment you get from beetles or something. That's even weirder.
Jason Wallace  15:25  Or ambergris, the sperm whale poop secretions or whatever that people collect for fragrances. Apparently, there's a lot of things that come out of other things rectums that we find very well. Okay, there's not a lot, but there's a few things that come out of other things rectums.
Elizabeth  15:40  More than you would think.
Brian  15:42  Oh man, I don't know what you were thinking, but with the argan oil, you can almost see the worker placement with your little goats,
Elizabeth  15:48  right? And little trees
Brian  15:53  and little piles.
Elizabeth  15:54  Theres a game there I just haven't figured it out.
Brian  15:56  Probably not turds, but some kind of seed emoji.
Jason Wallace  15:59  I don't know. You were saying that Ark Nova needed to have the little poop icons to indicate that the zoo was getting there.
Brian  16:04  So they have the break tracker, and I get that, and I know it's a cup of coffee. Which look, zoology is all about poop, right? If you are a zookeeper, your life is dominated by moving poop from one place to another. Which actually, I did want to mention somebody on our Discord username Kredal did point out to us that you have a cameo in Ark Nova.
Elizabeth  16:23  I do. Yes, I am the ornithologist card.
Brian  16:28  Now, how is that?
Elizabeth  16:29  It's pretty great. I kind of forgot that that was happening. So the company Feuerland, who's the publisher of Ark Nova originally, they are also the German translator for Wingspan, so they publish Flügelschlag, which is the German name of Wingspan.
Brian  16:49  I love German,
Elizabeth  16:50  and so they had like press materials from the rollout of Wingspan, and when they were working on Ark Nova, you know how all the cards have photos on them. Apparently, a lot of those photos are people that they know, and they reached out. They didn't really tell me that much about the game, but the graphic designer who I kind of knew and had hung out with a little bit was like, "We're working on this game. Can I use this photo that we had that we had sent to this German magazine, and can I put this in the game? It's one I think you'll really like. That's like the extent of what I do. Then, like a year later, this game shows up in the mail, and I had completely forgotten about that conversation.
Brian  17:33  It's like it is hugely popular, right? I mean, you probably have shown up in debates and ranking lists of like what the best sponsors are for Ark Nova on YouTube,
Elizabeth  17:42  but then when I play Ark Nova and that card, there's this whole thing over like, well, we have to play Elizabeth's card.
Jason Wallace  17:55  We can't be playing with Elizabeth and not play Elizabeth on the table.
Brian  18:00  You should get a discount if you play that card.
Elizabeth  18:02  Right.
Brian  18:03  You should get to do it for one less cost. It's like, come on, I'm already here. I should just have that ability.
Elizabeth  18:08  Right.
Jason Wallace  18:08  So, and you're still actively designing games. So, among all of this, do you have some favorite memory from the process of putting one of your games together? It's like some little magical moment or something where it just stands out as like you look back on it and it just makes you smile.
Elizabeth  18:23  Oh, there's too many because that feeling of when you change something and it just works and you know that's the way it's meant to be. That's such a good feeling, but it happens like over and over and over in the process of game design. Like I can't think of a specific one really, but God, there's nothing better than that feeling.
Jason Wallace  18:43  It feels like me after I've been wrangling code for several hours, and it suddenly works. So it's that solving that problem, that thing that was difficult, and you managed to make it work.
Elizabeth  18:51  Right, like I've tried five different approaches to solving this thing that's not working, or like, and then it suddenly will come together.
Brian  18:59  I'm thinking of the you know when you're sculpting right you're removing all the things that are not this game
Elizabeth  19:05  right sometimes it is that sometimes it's taking a thing out that's what you need to do
Jason Wallace  19:10  what about sort of the real world parallels so is there something you've managed to get into a game that you're just especially proud of like some bird in wingspan some mushroom in undergrowth or just something's like that was my pet thing, and I managed to get it into the game.
Elizabeth  19:25  I mean, there's a bunch of birds and wingspan. There cause I want them there?
Jason Wallace  19:30  That's fair. I mean, you're designing the game. You're allowed to do that.
Brian  19:33  Well, and I mean, you had to cut the list down. You couldn't do everything. I can't remember. Yeah. So like some things hit the cutting room floor, right?
Jason Wallace  19:41  Yeah. Is this instead of murder your darlings? It's murder your starlings. Yeah.
Brian  19:45  Oh God, Jason, did you have that one written down, or did that just come to the top of your head?
Jason Wallace  19:49  That was spontaneous. Thank you very much.
Brian  19:51  Okay. All right. Well, you're welcome. That's impressive. Okay, I'm going to ask you a silly question. Do you have a favorite end goal card for Wingspan?
Elizabeth  19:59  A favorite. Goal card. No one's ever asked me that question before.
Brian  20:03  Yay!
Brian  20:03  They always ask me my favorite bird. No, now I have to remember my favorite goal card. I don't know.
Brian  20:10  I have two that I really enjoy.
Elizabeth  20:12  Okay.
Brian  20:13  I like the one where you you're combining all the bird color names. Those are fun.
Elizabeth  20:18  Yeah, I definitely like looking at the names of the birds. I like the ones from Australia, where it's which ways are they facing from the issue of expansion.
Brian  20:25  Oh, really?
Elizabeth  20:26  Yeah.
Brian  20:27  Okay. Interesting.
Elizabeth  20:28  Oh no, is that a card or is that no? I think maybe that's the end of round goals. 
Brian  20:33  That would make sense. Like which birds are facing left versus right?
Elizabeth  20:36  Yeah.
Brian  20:36  And my other favorite is "the planner", where you get points for having a huge handful of cards that you haven't played yet. Yeah,
Elizabeth  20:44  I don't love those because it kind of encourages you not to play efficiently.
Brian  20:48  It's good for someone like me.
Elizabeth  20:50  Yeah.
Jason Wallace  20:52  So, how often do you play your games after they're released? We've talked to several designers where by the time a game gets released, they are so sick of playing their own game, that like it just collects dust on the shelf for years. Like, do you play your own games with other people?
Elizabeth  21:05  Sometimes, I think. Also, my friends are like scared to ask me to play my games because
Brian  21:12  do they just think you're gonna kick their butts?
Elizabeth  21:15  And they think I'm sick of them, which I often am when it first comes out.
Brian  21:20  So it's very considerate,
Elizabeth  21:21  but there's a decent amount of time between the time that I'm pencils down on the design and it actually comes out. Like the time that it takes to like really finalize it and then get it actually manufactured and across an ocean is like six months-ish often. So by then I've had a little break and I'll do it. And I like I'll play the Wingspan app sometimes just for fun, especially if I'm like trying to get my head back in the game before I start working on the next expansion. I'm always play testing the next Wingspan expansion. I play a decent amount of Wingspan, but it's like Wingspan that no one else is playing. It's a weird little setup. I don't know.
Jason Wallace  21:59  You're playing future wingspan. Playing
Elizabeth  22:01  future wingspan.
Brian  22:02  What are the expansions at this point? So it's Asia, Oceana. Is Europe out yet? There's
Elizabeth  22:07  Europe, and then okay.
Brian  22:08  So then we're running out of continents.
Elizabeth  22:09  I did the Americas.
Brian  22:11  Okay. Which,
Elizabeth  22:12  if you haven't seen, it has hummingbirds that are their own deck of little mini cards.
Brian  22:17  Interesting. Oh, that's so cute. Talk about abstraction. You make the the tiny hummingbird cards. That's great.
Elizabeth  22:24  They work in a whole different way.
Brian  22:26  Do you need to do the oversized, like tarot size ratite cards for ostriches and emus and stuff like that? They're just extra big.
Jason Wallace  22:34  I'm just waiting for the Antarctica mini expansion.
Jason Wallace  22:37  Yeah, yeah. With just penguins,
Brian  22:39  just penguins. It's the penguins. Penguins all the time.
Elizabeth  22:42  Yep. So I have Africa and I have Antarctica left. That's and I'm sort of working on both of them at once. Okay. As separate expansions, but just one came together faster than the other.
Brian  22:51  And then what comes after that? You're out of continents. Do you have to start doing different themes?
Elizabeth  22:56  I mean, I've been working on other games too. Okay. Yeah.
Brian  23:01  Cool. Cool. All right. Awesome.
Jason Wallace  23:03  Yes, I'm sure there's more to Elizabeth's life than just wingspan expansions. So
Brian  23:07  yeah.
Elizabeth  23:08  For the last seven years, there really has always been a wingspan expansion.
Jason Wallace  23:13  At least you've got job security. At least until you run out of continents.
Brian  23:16  Wingspan Atlantis edition.
Elizabeth  23:20  And we haven't mentioned Wingspan Pocket. Have you guys seen that that just came out?
Brian  23:24  I have seen that making the rounds on Instagram. So what is Wingspan Pocket? I saw the the cute little nest and everything. What's that?
Elizabeth  23:30  It's a little. It's a small box $20 game. You can play it in half an hour-ish.
Brian  23:37  Oh.
Elizabeth  23:37  And instead of the big player mat that has the three rows of birds for the three habitats. There's no habitats. You just have one row of birds, and you get to activate them every turn.
Brian  23:46  Huh. Okay. So it still feels like wingspan, but it's just like wingspan redux.
Elizabeth  23:51  Yeah. And the powers are simpler. The powers are mostly icons. Let's just like draw a seed card. Oh, and the food is on cards instead of dice.
Brian  24:00  Oh, that's fun! So it's all cards then.
Elizabeth  24:03  It's all cards. There's eggs
Brian  24:05  Oh fun.
Elizabeth  24:06  I tried to do the eggs on cards, and Jamie was like, "We can have eggs."
Brian  24:13  Awesome. We have a convention coming up. We should try to get and play that while we're there.
Jason Wallace  24:17  So when you finish one of these games, your gameography is well, like eight, nine games out in the world right now. We'll look at it. We'll link it in the show notes,
Elizabeth  24:25  plus a bunch of expansions.
Elizabeth  24:26  Don't make me count
Jason Wallace  24:28  But when you finish a game and you release it out into the world, this is maybe more of a philosophical question. What are your hopes for it? What's your metric for having succeeded at a game, not just in creating the game, but after you release it, what measures whether that game has succeeded for you?
Elizabeth  24:44  That is such a good question. I can't figure out the answer to it because my first game has sold two and a half million copies, which is a thing that does not happen ever. So I mean, you know, once in a decade, a game comes out that does that well. So I don't understand. What my metrics are supposed to be for my other games, I don't know.
Brian  25:04  It's like so. Jason and I are board gamers, but we do have friends that are not, and they say, "Oh, I know the bird game,
Elizabeth  25:09  right?
Brian  25:10  Like it has entered into the cultural space in a fun way,
Elizabeth  25:14  right? And you know, there's part of me that aspires to that with every game, but there's part of me that's just like, "Well, but you can't chase that level of success. That is just a recipe for unhappiness. So I don't know. I mean, a normal board game sells like 5000 copies, and my games, I think, have all done better than that. But
Brian  25:38  I guess it's like you know, comparison is a death of joy. So what do you look at? Do they make you happy when they come out?
Elizabeth  25:44  So, a lot of it's about like, is it well received? Like, yeah, I just want people to enjoy them. I want them to be accessible. Like, I really pride myself on having good rule books and relatively easy to learn games, but that have interesting decisions. Like, that's sort of the sweet spot that I'm aiming for.
Brian  26:03  We did think Fox Experiment was hard to set up, but once it was set up, it played great
Elizabeth  26:06  lot of stuff.
Brian  26:07  Yeah, yeah, there's a lot of stuff.
Brian  26:09  There's a lot of different card sizes.
Jason Wallace  26:12  So stepping a little bit away from board games per se, you've been very active in advocating for a more inclusive game design industry advocating for women, people of color, other people who are just not as represented in game design space, and a lot of these disparities are ones that we see in the sciences as well, where there's just systematic barriers where not everyone has an equal chance of getting into the system. And so, as someone who has not only been a very successful board game designer, but also someone who's been in Washington D.C. for 20 years doing policy work. What are your tactics and recommendations for trying to open up this space so it's easier for people of any background to get in to try to get rid of some of these barriers that keep people out who would be wonderful additions to the hobby, but just aren't able to get in because of the way things are set up,
Elizabeth  27:01  I mean, I think there's a lot of different levels to it. There's one level where game design is sort of fundamentally a luxury hobby. Board games are, in some ways, a luxury hobby. They're expensive, but there are ways to at least engage as a gamer. A lot of libraries have board game collections now. There's a lot of game stores that have game nights or just you know meetups that happen, so you can play lots of great games and never buy one. That is the first level barrier because then to become a game designer, generally those are people who've played a lot of games, and then game design is almost entirely done by people who are doing it as a side gig, so you need the luxury of time. And I think that one of the reasons that we see such a gender disparity historically in game design is the gender disparity in how people spend their time, and specifically around childcare and household labor. So that's a piece of it, and then at the other end of the process, once someone has designed a game, and there's lots of other things along the way that I have ideas about that I won't get into, but at the other end, you know, you've got publishers who have a strong incentive to sign games from people who already have published games because those designers already have a following, maybe, or at least sort of a proven track record, or you know relationships with people in the industry. They can get the meetings, and so at that point of a designer pitching a game to publishers and getting their game signed, I think there's a built-in bias towards the status quo.
Brian  28:43  I think that's a lot of industries, right? Publishing books or anything-it's the easiest way to publish a book is having already published one.
Elizabeth  28:52  Yeah, right. And like just thinking about 2016, I pitched Wingspan at GenCon in Indianapolis, giant board game convention. Almost every publisher comes to it, so you know you email people ahead of time and set up meetings. And I got three meetings set up before I got there, and that's one of them worked.
Elizabeth  29:10  But I knew no one at Gen Con when I went 10 years ago.
Brian  29:16  That must have been so intimidating.
Elizabeth  29:18  And now when I go to Gen Con, I can't walk down the aisle without passing multiple booths where I know someone that's working in that booth. That is just the embodiment of what I'm talking about in terms of like now I can really get a meeting. But even just from having been around for 10 years, I could get a meeting to pitch my game with most publishers. Right?
Jason Wallace  29:41  You've got the social network, the connections you need to leverage. So even if you only have a 33% chance return, you have so many more contacts. There's just going to be a lot more meetings.
Elizabeth  29:50  So in terms of what I think we can do on that end of the picture, which probably does have some parallels in STEM, I think publishers could be thinking more proactively about how they can be reaching out more, how they can be structuring their scheduling of their pitch meetings and things like that to make sure that they're getting new people in the door as well as established designers.
Brian  30:13  I know GAMA tries to do some stuff like this, but you almost need like a GAMA, like not a genius grant or scholarships is the wrong way of putting it, too-but just some way to support new designers.
Elizabeth  30:24  And I think that mentorship is another piece of the puzzle where we can help get some people who have ideas for games through that process of getting it to a pitchable state, and then through the pitching process, which is possibly the most terrifying part of the entire process. Although your first play test with people you don't know is also very terrifying. There's definitely points in the process where some handholding will help more people make it through that gate.
Brian  30:55  I guess that's what things like Unpub are for, right? Helping to build that network, build those skills, help to build those connections, right?
Elizabeth  31:01  Yeah, and Unpub has a mentorship program. There's some other ones in the industry as well where you can sort of hook up with other game designers. I'm now on the board of the Tabletop Game Designers Association, which is another organization that's like trying to just help people make it through the process.
Brian  31:19  Is that different than GAMA? Are you a member of GAMA as well?
Elizabeth  31:22  Yeah, I might have let my membership lapse 
Jason Wallace  31:25  For our Listeners GAMA is the Game Association Manufacturers of America.
Elizabeth  31:31  Something like that. They are.
Brian  31:33  It's the Game Manufacturers Association
Elizabeth  31:34  They've decided to go IBM, and like their acronym doesn't have a meaning anymore.
Brian  31:38  No, it doesn't make sense.
Jason Wallace  31:38  Okay
Elizabeth  31:39  So GAMA is the trade organization that started as being like the publishers and manufacturers. They have created sort of branches that include designers and other creators. It costs $300 to join Gamma as an individual, and $300 if you're Asmodee, and it rubs me the wrong way.
Jason Wallace  32:01  Asmode being one of the big publishers who they're a company and they're one of the biggest distributors there. So it's like if it costs me and Google the same amount to join an organization, maybe we should rethink that pricing structure.
Elizabeth  32:13  Exactly.
Jason Wallace  32:14  So do you have any specific advice for aspiring game designers who are listening to this?
Elizabeth  32:19  My biggest advice to new designers is just you got to get your game to the table. Like thinking about it will not get you very far because there's always something you don't think about until you actually try to play it, and then realize that like the 10 hours you spent journaling about what this game was going to be was all based on a premise that doesn't work, and you need to fix this thing, and now you have to rework every card that you thought of. Just make like 20 cards and try something.
Jason Wallace  32:47  That sounds like the voice of experience speaking.
Elizabeth  32:51  Maybe?
Jason Wallace  32:53  All right. So shifting a bit, what are some of your favorite games that you haven't designed? So what are the favorite games you like playing that come from other people?
Elizabeth  33:00  I've probably played Race for the Galaxy more than any other game.
Brian  33:04  Have we played that?
Jason Wallace  33:06  We have not. I don't think so.
Brian  33:07  See, we have sort of put ourselves in this very narrow focus with this.
Elizabeth  33:11  Right, It would not fit in your narrow focus.
Jason Wallace  33:15  That's okay. Some of my favorite games don't either. 
Brian  33:17  Yeah we don't just play games for the podcast. We do do things for other just for fun sometimes.
Elizabeth  33:23  I've been playing a lot of Apiary lately by Connie Vogelmann,
Brian  33:26  designer of Wyrmspan. Yes?
Elizabeth  33:28  designer of Wyrmspan. I do love Ark Nova, which we were talking about. I like terraforming bars.
Jason Wallace  33:34  Have you ever tried or heard of a game called Holotype?
Elizabeth  33:38  No.
Jason Wallace  33:39  It's one we discovered through this podcast, it is a worker placement game about paleontology, and we love it because not only does it have tons of cool like paleontology facts and stuff in there, but it's also extremely well balanced. We did a special interview specifically because one of the designers is a computer science guy. He programmed his computer to play the game 10,000 times a minute, so he could play test all the point values and make sure they were balanced.
Elizabeth  34:03  Oh my god,
Jason Wallace  34:06  that would be my recommendation. Then
Brian  34:08  it's not a game about dinosaurs fighting. It's a game about digging up fossils, classifying them, and publishing them as holotypes in a journal. It's a game about being a paleontologist. It's really good.
Elizabeth  34:20  The publishing makes me think of I love Search for Planet X.
Brian  34:25  Oh yeah, we played that too.
Elizabeth  34:26  And Search for Lost Species.
Brian  34:28  That we've not.
Elizabeth  34:29  I'm a big fan of logic puzzles in general, so that was definitely scratch and itch for me.
Brian  34:33  Yeah, we had a a notorious episode where we played Turing Machine, where I was like, how is any of this working? I think it took three full playthroughs before I understood what you're doing,
Brian  34:44   Like how it physically actually works?
Brian  34:48  Yeah, but more than that, it's like if you mess up, you're just you're boned. You're not going to fix it at that point, and that's true for Planet X as well. If you made a logical mistake, well. Tough luck.
Elizabeth  35:00  Yeah, it's true.
Jason Wallace  35:02  Okay, well, I we got to wrap up now, Elizabeth. Thank you so much for coming on. This has been a great conversation. If people want to look up more about you or your games, where can they find you? Where should they look for information?
Elizabeth  35:13  So I have a website, which probably just comes up if you Google me, but it's Eliz Hargrave. So just the first four letters of my first name because my name is too long. So elizhargrave.com will get you to a little landing page that has links to my blue sky and whatever else. I have a couple newsletters and things like that.
Jason Wallace  35:32  All right, and we will definitely link that and a bunch of other stuff we've talked about in the show notes. So with that, we're going to wrap up. So thank you again, Elizabeth. This has been a joy to have you on! Thank you, listeners, for being with us. And go out, find some mushrooms, some birds, or some butterflies, or some seashells. And in the meantime, have a great month and great games,
Brian  35:50  and have fun playing dice with the universe. see ya! 
Jason Wallace  35:52  This has been the Gaming with Science podcast, copyright 2026. Listeners are free to reuse this recording for any non-commercial purpose as long as credit is given to Game with Science. This podcast is produced with support from the University of Georgia. All opinions are those of the hosts and do not imply endorsement by the sponsors. If you wish to purchase any of the games we talked about, we encourage you to do so through your friendly local game store. Thank you and have fun playing Dice with the Universe.
Transcribed by https://otter.ai

#Domestication #TheFoxExperiment #ElizabethHargrave #Dogs #Evolution #BoardGames #Science
Summary
Foxes, wolves, and corn, oh my! We're talking domestication today, all revolving around The Fox Experiment and two Russian scientists' attempt to understand how we turned wolves into dogs. We're joined by Dr. Angela Perri, an expert in dog domestication, and cover what domestication is, how wolves became dogs, how that probably kickstarted a lot of other domestication, how much a domestic fox costs, and a surprising amount of about corn. So grab any furry friends you have and settle in for this canine-focused episode of Gaming with Science.
Timestamps
00:00 Island foxes and ancient corn
09:35 The Fox Experiment (the game)
15:48 The Fox Experiment (the actuality)
23:31 How did all this happen?
26:20 Dog domestication
34:58 How relevant is the fox experiment still?
40:30 Domestication across species
43:31 Plant domestication
48:22 Nitpick corner
53:20 Final grades
58:50 Signoff
Links
The Fox Experiment (Pandasaurus)
Big brains for Channel Island foxes (PLoS ONE)
Two teosinte ancestors for maize (Science.org)
Teosinte vs modern corn (Wikipedia)
Domesticated Silver Fox (Wikipedia) (Includes descriptions of the experiment)
Dogs as gifted word learners (Science.org)
Italian brown bears evolving to be less aggressive (Smithsonian Magazine) 
Find our socials at https://www.gamingwithscience.net 
This episode of Gaming with Science™ was produced with the help of the University of Georgia and is distributed under a Creative Commons Attribution-Noncommercial (CC BY-NC 4.0) license.
Full Transcript
(Some platforms truncate the transcript due to length restrictions. If so, you can always find the full transcript on https://www.gamingwithscience.net/ )
Jason Wallace  0:06  Hello and welcome to the Gaming with Science podcast, where we talk about the science behind some of your favorite games.
Brian  0:10  Today, we're going to talk about the Fox Experiment by Pandasaurus. Hey, welcome back to Gaming with Science. This is Brian.
Jason Wallace  0:20  This is Jason,
Brian  0:21  and we've got a fantastic guest for us, Dr. Angela Perry. Can you introduce yourself, please?
Angela  0:26  Sure, thanks. My name is Angela Perry. I am an archeologist by trade, and a specialist in the human canine relationship, ancient DNA, and the archeology of the human and dog existence,
Brian  0:42  this is super cool, and again, is super perfect for this game. Thank you, David Muscato from the Common Descent, for pointing us in your direction, and thank you for agreeing to come on and talk to us about a nerdy board game.
Angela  0:54  Of course.
Brian  0:56  Okay, so before we get into the game, we usually start with a science banter topic. We usually let the co-host go first if they have one. If you have something you want to share with the listeners, that's great. If you don't, I'm sure Jason has one waiting in the wings.
Angela  1:10  I thought, what better topic to talk about than foxes, since we're here, and I'm really interested in not only canids but in understanding kind of island theory, island domestication theory, and I was reading something recently talking about the Channel Island foxes off of the California coast on the Channel Islands. They have a special fox that lives on the Channel Islands that is a lot smaller than mainland foxes. We always think of you know a smaller fox, smaller animal having a smaller brain across the board. Dwarfism that goes along with living on islands, but they actually found that the brains of the Channel Island foxes are bigger than their mainland gray fox counterparts, which they think more research to come is related to the mental stamina needed to figure out kind of complex living on this difficult, rigorous location on on the islands off of off of California. So I thought that was pretty cool. Usually we would think like smaller animals, smaller brain, but they actually have a bigger brain. Pretty cool.
Brian  2:18  That's really cool. I don't think we've have we had a chance to really talk about island evolution yet? How it seems to make small things get bigger, big things get smaller, and everything gets weird.
Jason Wallace  2:27  We have not yet. No,
Angela  2:28  it's a good one.
Brian  2:29  I'm gonna have to like actively go out and look for a game about that, or maybe this is just what we talk about when we talk about when we do a Darwin Day game. We can talk about it then. What about you, Jason? Did you bring something?
Jason Wallace  2:39  I did. So we're probably not going to come back to this at all the rest of the episode, but I want to talk about plants, and of course my favorite plant, maize, corn. So there was a study. 
Brian  2:49  You're doing the thing that I used to do, where I just make everything about onions. So now we're just going to make everything about corn for the rest of the season. Okay, fair.
Jason Wallace  2:57  So, but this is a study that came out about two years ago, now out of the Ross-Ibarra lab in California, someone I know through the maize community, looking at the domestication of maize, and they're using a lot of the whole genome sequences where you can get the entire genomes of 1000s of maize lines, where you can get ancient DNA out of archaeological sites to sort of reconstruct the history of domesticating corn. They found something that was really surprising: is that there was actually a two-wave domestication. So you initially got maize domesticated out of a a precursor named Teosinte and a specific variety of it called Parviglumus, which is in sort of like the lowlands of southern Mexico, and apparently about 4000 years after that initial domestication, it hybridized with a different teosinte called Mexicana that is in the highlands. So it's up in the higher. It's colder, shorter growing season, kind of rougher environment, and apparently that hybridization was super important because that hybridized maize then spread throughout the Americas and basically either displaced or hybridized with all existing domesticated maize. And so, pretty much all the maize, all the corn we have today, is descended from this sort of two-step hybridization, where you had your initial domestication, and it was like that for 1000s of years, and then you had an introgression, a hybridization with this related cousin species that suddenly, I guess, supercharged it because it was whatever it gave it gave it such an advantage that it then spread everywhere.
Brian  4:35  This new maze is so hot right now.
Angela  4:37  Also, mirroring the story of gray wolves. Gray wolves also have a similar path of like a single stock population of gray wolves taking over the world, and now being the kind of all gray wolves being the descendant of a of a population like that. So, oh, is
Brian  4:55  that right? Oh my goodness! So they have like a severe bottlenecking event, like humans did too, right? Yeah.
Angela  5:00  Yeah,
Brian  5:00  Jason, can you describe Teosinte for those people who would not be familiar with it? Because I don't know what you're thinking of, listener. If it
Jason Wallace  5:08  looks like corn, you're probably not thinking about it. Yes. So Teosinte is the wild ancestor that gave rise to maize over many, many centuries of domestication. It took a good chunk of the 20th century for us to figure that out for sure, because teosinte does not look like modern corn. So modern corn, you have this nice big ear, hundreds of kernels on it. The plant is like tall and erect, and it's got like the the the male anthers that shed pollen at the top and the female ear down at the bottom. Teosinte is basically a bush that has like little bits of flowers everywhere, and its ear is a single row of like these like trapezoid-shaped kernels that are stacked on top of each other that are literally surrounded in a rock-hard fruit case. It's called. Like I've heard of people having to get these things open with a sledgehammer. It was one of those things where it looks so different from modern corn. It actually took several decades of work for people to decide that oh no no no this is this actually is the variety not some weird thing that went extinct that we no longer know or some weird hybridization of it it actually is this and people have now tracked down the handful of large effects genes that are important for that for getting rid of the fruit case for making more rows of kernels for making them bigger and such, for changing it so that instead of having a bush, you have mostly a single central stalk. And then there's hundreds and hundreds of smaller genes that kind of feed into that process. Actually, the lab that did this domestication paper I mentioned, they have done a lot of the work identifying a lot of the the smaller effect genes, the big effect ones, were identified several decades ago, but the small effect genes have been only been identified more recently because they're much harder to find.
Angela  6:48  Sounds like Jason is ready for the farm fox experiment. We're on trend here.
Brian  6:55  So, like domesticated wheat still just kind of looks like a grass, right? But like maize is a grass. It doesn't look like that, and I think that's because the wheat breeders are lazy. I want wheat that is the size of an ear of corn. Like, come on, breeders, let's get on it.
Angela  7:09  Do people still like indigenous populations still use like native teocente?
Jason Wallace  7:14  To my knowledge, no. I think teosente is mostly considered a weed that's kind of on the edges of the cornfield. Okay, there. I mean, there is some gene. They are interfertile. There is some gene flow, but the things that's kind of halfway between is neither really good at being tiacente or good at being corn, and so it's not like the the initial hybrids are not great. But you do have some gene flow between them.
Angela  7:38  Tell us about. Sorry, I'm I'm going way off topic now. I'm sending us down a rabbit hole, but I'm wondering. Tell us about heritage popcorn and all of these things that we see, like purple, purple popcorn, and all these things that we believe are like heritage maize. Heritage, yeah, Jason,
Brian  7:55  tell us about your heritage corn breeding program that you are actually working on.
Jason Wallace  7:59  Okay, this this could open. This could be an entire other episode, to be honest. 
Angela  8:04  I'm ready for it. Heritage popcorn.
Jason Wallace  8:06  The short version is that Native Americans used maize as a staple grain for 1000s upon 1000s of years, and they adapted it to every environment from Canada all the way down to the bottom of Argentina. And so there are literally 1000s upon 1000s of traditional varieties in every color of the rainbow. Literally, like I, I have a rainbow made of corn that has every single color, and plus like white and brown and black and such. And modern corn has been selected to produce very well in a modern environment. And at least here in the United States, like we don't like we eat sweet corn. We feed a lot of corn to our animals, but we don't really appreciate corn itself. If you go down to Mexico, like they have all sorts of different varieties, they different colors. They appreciate them. The native populations, different colors have different spiritual significance. We have gotten kind of divorced from the original like cultural meaning of corn, but there's a lot of them out there. And if you check the seed catalogs, you can find some really cool ones. I'm, as Brian said, I'm actually working with some in my field this summer, trying to see if I can move around some of those color genes and get them more up to like modern performance standards. Because a lot of them, like they look really cool, but a lot of them just really suck when you put them in a field. Yeah,
Speaker 1  9:24  cool. Shout out to my grandparents who are corn farmers in Kansas. Oh, cool! Look at all
Brian  9:30  these connections. Okay, so you guys want to talk about a board game?
Speaker 1  9:34  Yeah. Sure.
Brian  9:35  All right, let's do it. So the fox experiment was designed by Elizabeth Hargrave, who some of our listeners certainly will know as the designer of Wingspan, as well as Jeff Frasier, who, according to his website, specializes in board game rulebook design. It's published by Pandasaurus. It's for one to four players for 10 and up. Certainly, Jason's girls could play without any issue. Your. Your mileage may vary based on your individual 10-year-old. The game is inspired by a true story. is probably the best way to be thinking about this.  and 's Russian silver fox domestication experiment that was done in the 1950s in Novosibirsk. So, how does the game work? Players, you're taking on the roles of fox breeders or scientists, you are trying to breed friendly foxes, and that they will develop other traits at the same time: floppy ears, curly tails, spots, barking, or friendly vocalization. I guess not everybody likes barking, but it is a distinct thing. The way that you play the game, you're going to play over five rounds, each one representing a generation. So between generation one and generation five, this is where you'll sort of get to breed your super elite foxes. Every turn, you're going to pick a male and a female from the kennel. Those are going to have trait dice that are based on each of these four traits that I mentioned: the ears, the spots, the vocalization, and the curly tails that will generate a dice pool for you. You then roll them to create symbols that basically represent the traits of the offspring. So you'll mark them down. This is a roll and write. So you roll your dice. You got a little card with a little dry erase marker. You mark in how many of those traits you'd filled out. You get like tokens based on the traits that you've generated. It generates a new dice pool for you. At the end of the turn, your pups go into the kennel, and can be recruited either by you or by an opponent. And you're trying to sort of like achieve outcomes, like get a fox that has a certain amount of spotted coat trait, for instance.
Jason Wallace  11:37  Longtime listeners will probably recognize some of this as being very similar to the game genotype that we talked about previously, which is another one where there is a drafting mechanic where you roll a bunch of dice. In that case, for Mendel's peas to try to get certain traits, and then you're trying to check off certain goals. I'd say the main difference. Well, okay, there's a bunch of differences, but the main difference for this particular part of it is that in the fox experiment, you actually can move selection forward in a specific direction because the offspring you make then become potential parents for the next generation. And so, as you breed foxes that are more domesticated, you can then use those as parents and push the next generation even further along.
Brian  12:18  Another big difference from genotype: genotype actually uses Punnett squares to sort of track dominant and resistant traits. Fox experiment, we're kind of doing vibe-based genetics a little bit. The other thing to consider is that we've also got this friendly dice that acts as a sort of a wild die that you can use to help build other traits, like how friendly they are. You actually get like a "Who made the friendliest foxes" generation bonus. You have patrons that are looking for specific things. As
Jason Wallace  12:46  with many games, there's several different ways of earning victory points, so can kind of pick and choose which one. Although, since there are only five rounds, it actually goes pretty fast. It does, and so you have to get those points together pretty quickly, or at least line them up pretty quickly in order to get them, because you can be at the end of five rounds before you really realize, like, oh wait, I need to make sure this is all set up.
Brian  13:07  Yeah, you don't get that much time because, again, the other thing that's interesting, and Jason and I experience this. This game setting up the board. This is an extremely space hungry game. You know, we have our bowl of chips factor. There is nowhere on this table for a bowl of chips. Lots of dice, lots of tokens, lots of cards, lots of everything everywhere. takes a while to set up, but then once you get going, it's actually pretty snappy. Each round only takes-I don't know-does it even take 10 minutes to do a round? No,
Jason Wallace  13:31  it was pretty fast. There's a quick draft that you do, and then everyone does all their rolling and stuff together. There's little tip cards that have you walk down through the steps, and so yeah, it was very intimidating to set up because there's like all these pieces that oh my goodness I have to track all of these and then once we got going, it's like oh the actual round structure is pretty straightforward and simple.
Brian  13:49  Jason, do you feel like there's anything I missed in particular?
Jason Wallace  13:51  I think there are some nice touches for this. So the arguably cutest part of the game is the individual fox meeples that you have.
Brian  14:00  Oh, absolutely! Which
Jason Wallace  14:01  are not just fox meeples; they're actually four distinct shapes of fox meeples that every player has in their color. So you have 10 fox meeples, and everyone has four different shapes of them. So you can have these cute little foxes. There's no mechanical reason for it. It's one of those tiny little things that doesn't have to be done in a board game, and yet is an important part of like the tactile enjoyable experience because I looked at like oh this is so cute I like this game more now because it has four little fox meeple shapes for me to look at
Brian  14:30  this is a terrible analogy but this is like the four shapes of chicken nuggets I noticed in the
Angela  14:37  video as well I want to shout out the the video example that you guys sent me of it to to describe how you play the game. The woman was clear to say that she didn't agree with meeples. She would like it to be meoxes or moxes. It
Brian  14:54  was if meeples is short from my peoples, and these are my foxes, and these are not feeples or. foxeeples, these are moxes.
Angela  15:02  Moxes. Whereas you said, I appreciate that.
Brian  15:07  This is one of those games where you have three distinct sizes of cards. You got the little tiny cards. You got the regular size cards. You got the oversized cards. So you actually have three different, not just card decks, but types of cards that get put into about four or five different decks. I'm not kidding. Setup for this game is a bit much. Definitely, like it's inconsistent with the play experience. The play experience is pretty fun and quick and easy. The setup is oh my god, what even is this piece right here?
Angela  15:34  Maybe it's trying to get you to recreate all the steps of preparing your scientific experiment. Maybe the thought processes that go through. 
Jason Wallace  15:43  Yes, oftentimes the setup ismuch more arduous than the actual execution in those cases.
Angela  15:47  Yes.
Brian  15:48  So again, this game is supposed to be inspired by the Silver Fox domestication experiment. So let's talk about that experiment now, because there's one thing that's going to jump out at you right away about the actual experiment. This was an experiment that was done, like I said, in the 1950s in Novosibirsk, based on this hypothesis that domestication of dogs-so much difference in morphology, shape, everything like that-but was based on this hypothesis that the core selected trait was actually docility, friendliness, tameness. I'm going to use these all sort of interchangeably. I don't know. I'm sure that there are meaningful differences between them. A combination of lack of aggressiveness and interest in humans, and that was it. The idea is, if we select just for behavioral traits, will the other traits emerge out of that sort of by proxy? I think the hypothesis was that domestication would would make changes in hormone processes that then would lead to many of the other things that we associate with domestication. So the selective procedure was pretty specific. There was really only a single trait that was selected. So it was only for tameness towards humans. They didn't select for fur color, body shape, ear shape, or tail. They also didn't do anything to train the foxes, which basically means that these foxes didn't interact with people at all. They spent basically their whole lives in cages. That was considered an important part of the experiment, which I guess makes it kind of sad since you're making friendly foxes that don't get to interact with people.
Jason Wallace  17:15  And we should say this was this experiment happened several decades ago. It would probably not fly today, not under those conditions anyway.
Brian  17:22  Probably not. No, I think we talked about this when we talked about Ark Nova and the development of zoos. We hadn't really invented ethics yet.
Angela  17:29  I was like, didn't go to the board for review for sure.
Brian  17:32  The original foxes actually came from fur farms, which I know some people have then said that that might have contributed to the experiment.
Angela  17:39  There is a debate about this about whether it was already a kind of captured, isolated population that they were beginning with.
Brian  17:47  Okay, the selection was let's see. At one month of age, every fox cub was tested repeatedly. They were offered food by hand. The handler would attempt to pet the fox and attempt to handle it. They observed if it was if the fox would approach or avoid the the researcher. Each cub was assessed inside its cage, and then in an enclosure where it could either approach the the human or other foxes. And the scores were based on their willingness to approach a human, whether or not they tried to bite the person or acted fearful or aggressive, and then also if they would seek out humans if they would actually seek out human contact. the The highest class, these sort of domesticated elite, they would actively seek out human attention. They'd whimper to attract people. They would sniff or lick their handlers, and they sort of develop these sort of more friendly characteristics. And within about six generations, they sort of had a population of these domesticated elites. Now, what's interesting is that some other traits did start to appear. So, for instance, by the fourth generation, tail wagging behavior had appeared. Something that's not in the game is that actually their reproductive patterns had changed. They had shifted to earlier in the season. I think they started developing coat mottling, which then, from at least what I read, the idea was that the melanin and adrenaline use the same biochemical pathway. So this may have had something to do with why the mottling appeared.
Jason Wallace  19:12  So melanin is the kind of brownish color in your skin and hair and such. Adrenaline is the fight or flight hormone, and so the idea being that adrenaline is keyed to aggression and melanin to color. There may be some sort of trade-off there.
Brian  19:27  Droopy ears and sort of other things like facial crowding. A lot of these things that we associate with domesticated dogs started to appear in the foxes under admittedly relatively severe breeding selection, where I think only 20% of the foxes were retained between generations. Basically, the the conclusions of the experiment were that you could end up with a lot of domesticated like traits in terms of morphology through single selection of behavior over a relatively short period of time. Now, I do want to point out something that is a. Key difference between the game and the experiment. In the game, Jason, what are you selecting for?
Jason Wallace  20:05  Everything but tameness. You're selecting for the toast and the ears and the barking and the tail.
Brian  20:11  Right. In the actual experiment, the only thing you're selecting for is friendliness. The only thing you're not selecting for in the actual game is friendliness. So it's actually flipped on its head. I think it's a it's an understandable change to make, as
Jason Wallace  20:24  you said, inspired by a true story.
Angela  20:26  Inspired, yeah.
Brian  20:27  It's an interesting experiment. has a long history. I think I know that they sort of ran into funding considerations at some point. I I believe that some of these foxes may still be around. I know there was even a push to actually have these available to people as pets, although I don't know if that was ever successful or not. It
Angela  20:45  was, from my understanding, is that when they ran into funding challenges, they began to sell designer foxes. And at one point, I can't remember what year it was, but it was on the cover of National Geographic, one of the domesticated foxes, in a quite lavish-looking, you know, Russian apartment where Russian elites and others were purchasing these $8,000, $10,000 designer foxes as as pets, you know, in Russian blue and all these dramatic colorways for a time. It was quite the fashion to get yourself a designer fox and put it on a leash and walk it around, and I expect that if you wanted one, you could probably get yourself one still.
Brian  21:30  The $8,000 sounds like a lot, but I know some designer breeds of dogs would be comparable. Yeah,
Angela  21:35  yeah, I would say that given the cost of some dogs now, they probably have increased their prices are showed if they haven't already on the foxes.
Brian  21:43  I think I did remember reading that while the foxes would tolerate a leash, they're not exactly enthusiastic. They don't love
Angela  21:48  it. They definitely don't love it.
Brian  21:50  What was the other thing? It said that foxes have a very distinct smell that they also lost during domestication, and that there was another study that one of the things that dogs can do is they're really good at understanding human body language, or particularly facial body language, and that the foxes evidently did pretty well on that too. So,
Angela  22:08  yeah,
Brian  22:08  they were they were bred for friendliness, but they also just became better. I don't know. I don't want to say attuned, but I don't really know what else to say. It's like they could understand human gesturing.
Angela  22:18  Yeah, non verbal gesturing, like dogs. I've quite a few friends are in the canine cognition world, and dogs are really great at reading eye movements and calibrating the whites of your eyes of where you're looking and interpreting kind of what what you mean by that and and learning language. I was one of my other kind of facts. I was thinking about was a paper I saw come out in January talking about that some dogs are called like gifted word learners. Some of these dogs that you hear about who can pick up, you know, matching items with a word very quickly. That they can passively by listening to humans just talk to each other identify the name of an object that humans are talking about to the same degree as a 18 month old child, so a year and a half year old, just not even talking directly to them, and not even like holding the item necessarily, but in in passing they can identify what humans are talking about, and so I think foxes learn the same trait of nonverbal communication on the kind of movement, pointing, eye movement, things like that as well.
Brian  23:24  They do significantly better at that than some of our close relatives. Like chimpanzees, don't do this very well, right?
Angela  23:30  Yes.
Brian  23:31  Okay.
Jason Wallace  23:31  I actually have a question, and this is specifically why we need you on here, Angela. Why is this? Like, why did this experiment have all these results?  Where selecting just for friendly foxes. Had all these other knock-on things. I've heard this called domestication syndrome. I don't know if it's just in like foxes and dogs, or if it's all sorts of other things in mammals. Like, what happened?
Angela  23:52  It's a good question. I think that their intuition, Belyaev & Trut, of if we select for this behavior, will we see these kind of phenotypic traits kind of follow along was actually quite ingenious, and using an isolated population like foxes to do that was really interesting. With wolves, with wolves who are the kind of ancestors of dogs, we often think about how similar humans as hunter gatherers would have been to wolves, right? Animals who hunt in packs. We're daylight hunters of of animals that are larger than ourselves. We work together in many ways, not only with hunting but of care and cooperation, care of young, and that there may be some similarities evolutionarily of how we moved across an environment that's very similar to wolves, and maybe similar hunting patterns, similar kind of culture. You know, we talk about wolves as one of these animals that has culture, like we do, because you have wolves who are. Very familiar with hunting a certain type of animal. There are deer hunters, and then you have wolves who are, you know, moose hunters. And teaching a moose hunter wolf how to be a deer hunter wolf is not necessarily as easy as you would think. And so maybe it's one of these animals that has has culture and operates within a group dynamic, similarly to the way we do, and we can imagine everyone's seen, you know, National Geographic videos of wolves hunting and moving across a landscape together, and their sense of like vocalizing to each other and watching each other, and having these small movements that signal to each other, like their their moods and and where they stand in a in a hierarchy within the group are not dissimilar I think to the way that we operate as humans taking nonverbal cues from each other and eye movements and things like that so I think there's a lot of basis of that
Brian  25:55  and I guess we're also both sort of endurance runners too so basically wolves and humans seem to occupy almost the same niche, which you'd think would lead to competition.
Angela  26:04  I think it probably did lead to competition in some places, also leading to scavenging off of each other in some places, and perhaps unsurprisingly, eventually leading to the relationship that became the domestication of dogs. You know that close relationship.
Brian  26:20  Okay, I have to ask. Let's let's do the story because what the what were the likely steps in the domestication of dogs? I think that maybe people have an understanding of selective breeding, but domestication probably wasn't exactly that. Like the the the experiment on the silver foxes was domestication speed run, yeah, extreme selection for a very specific purpose, so that's probably not what happened for most domestication, right?
Angela  26:45  Probably not, and it would be great to hear Jason's version of this on on the plant side. But as far as we know, dogs were the first domesticated anything, right? Plant, animal, anything, and the concept is easy for us now to think about. Of course, you could just domesticate. I mean, the concept of domestication would have been, you know, a novel concept to to the peoples who who eventually domesticated dogs. And I think sometimes the domestication has been talked about as if it was an event. Like we woke up on a Tuesday, we said today's the day we're going to get these wolves and we're going to turn them into dogs today. Most likely, domestication of dogs and probably many other animals and perhaps plants as well was, you know, a process that was full of starts and stops and failed dead ends and maybe meaningful attempts. In the example of the farm fox experiment, I think speaks to a very specific hypothesis of domestication, which is that it was intentional, and that the prevailing theory for domestication of dogs for a long time was that, of course, we saw these adorable wolf pups out in the environment, and we perhaps found them orphaned or had killed the parents and picked them up, and and went back to our camps and raise them as our own in a very call of the wild like idealistic sense. I laugh because I have so many friends, as I said, who who work with modern wolf populations and kind of canine cognition science. Who will tell you that it is not as simple as taking a wolf pup back home and then you live together like a clan of the cave bear-like existence. You know, it's not it's not that easy. And the idea that they would have been doing this regularly enough to kind of recreate the farm fox experiment, I think, has kind of gone by the wayside. But that idea of intentional domestication by taking wolf pups was the kind of prevailing theory for a really long time,
Jason Wallace  28:41  and my understanding is that the current one, at least the current one I know about, is more about this scavenging that you talked about. That the wolves would have been scavenging off of our midden heaps, the things around our encampments, and that would sort of incidentally select for wolves that tolerated humans better, that were a little bit friendlier, and that probably over several 1000 years you got sort of a subpopulation of wolves that kind of hung around our periphery, and somehow that eventually became more dog-like. I don't know the middle steps there. I just remember when I was a postdoc, there was someone in a neighboring lab working on dog domestication, and she presented the results of like, oh yeah, there have been. It turns out that street dogs have been street dogs forever. They're not like feral domesticated dogs. They've just been a separate population of dogs for 15,000 years or something like that. Oh wow! More
Brian  29:33  like cats then. Yeah, just sort of adapted to live around people.
Angela  29:36  Yeah. Well, you could think about you know a New Guinea singing dog or dingo, or what we call village dog-the yellow medium-sized village dog of every place you've you know ever visited. The
Brian  29:49  platonic ideal of dog,
Angela  29:51  dog, and so this idea of the scavenging hypothesis is the more prevailing theory these days. Every Scientist has a stand idly in the shower and zone out and think about why did this thing happen and like that's their shower question of like that they just mull over over and over in their minds and for me it's like the how why when who of dog domestication and trying really a search for like the driver of dog domestication why now if we imagine a world in which humans and wolves probably lived side by side across Eurasia for generations, why why now? Why did domestication happen when it happened and where it happened? And I think the driver of putting humans and wolves together in an isolated location with limited resources and a driver to become closer and closer and closer, and scavenging perhaps off of each other, and leading to you know going back to the farm fox experiment, a situation where we know lots of people even today who live in close proximity to wild animals and dangerous wild animals that don't necessarily kill them or fend them off. Right, I can think about people who live in Alaska around bears or, you know, other similar large predators who have just become accustomed to having these animals kind of live on the periphery and kind of you stay away from us, we'll stay away from you. Type scenario, but seeing them on a regular basis and the one-off dangerous bear that wanders into the village may be killed. The ones who are kind of on the periphery and behave themselves get get to live, you know, another day. And it's very similar to the idea of the farm box experiment of testing each other, culling for the ones that cross the boundary, and I think that with with the scavenging hypothesis, the idea that you allow wolves to come closer and closer to your encampment, humans are increasingly messy and and staying in one place for longer period of time, building up trash piles, and of course, wild animals searching for resources will eventually find human trash as they always do, and and scavenge off of it. And I think that the idea that this is probably what led to that reduction of the fight or flight in both humans and wolves, allowing for that tension between them as predators to kind of release a bit. The raising of of more and more generations of wolf pups who would have been born near humans, be used to having humans in the local environment, and be willing to potentially be closer to humans,
Brian  32:43  so you can kind of imagine the scenario where someone just takes a scrap of something they don't want and throws it to a friendly wolf that happens to be around, and that's not dissimilar to what we happened in the fox experiment. Although it would have taken a lot more time for that to sort of spread across the gene pool. I wish I remembered more details. There's a particular subtype of of Eurasian black bear that I think has been. I'll have to. I'll find this for the show notes, but it's the same thing. It's basically has lost most of its aggressiveness, is much smaller, and lives quite close to people. I think it's in Italy. Does this does this ring a bell to either of you? Nope. And but I'll find it. But basically, this is sounds like what might have happened with the wolves. Is basically the bears that were aggressive were killed, and the ones that were less of aggressive have been allowed to sort of stick around. We're slowly like a domestication like experiment happening with bears, I suppose this is narrator Brian. What I was thinking of was a study of a population of Italian brown bears. We've posted a link to a story in Smithsonian Magazine on the subject.
Angela  33:51  Yeah, or urban foxes in the UK. You know, when I lived in the UK, we have there were foxes everywhere, and they, you know, humans had just gotten used to having foxes run around the cities, and it's a kind of "we leave you alone, you leave us alone" type scenario.
Jason Wallace  34:06  So, back on dogs, do we know when and where dog domestication occurred?
Speaker 1  34:11  We don't. We don't know 100% We have lots of hot breadcrumb trails. I'm biased in that I write. I write. I'm biased that I write papers saying I think I have an idea of where it is, and so for myself and my colleagues, lots of things are pointing more and more and more to kind of the Beringia Siberia location. Beringia is the kind of north northeastern region of Siberia. That's where we think people kind of had this standstill for 1000s of years, waiting out the nastiest part of the last ice age, and eventually the ancestors of Native Americans made their way east across the Bering, what we call the Bering Land Bridge, into the Americas.
Brian  34:58  So I'm just curious. You know, this is not our area. Is the domesticated silver's fox experiment still considered important in a modern context? Is it still part of the conversation about domestication and domestication syndrome?
Angela  35:10  It is. I mean, it's referenced quite a bit, as you said. It's probably an experiment that would never happen in modern period. There are a lot of criticisms of it, obviously, but I think it was instrumental in helping us understand on a very controlled scale of what could happen to a canid if certain pressures were put on it, and you you culled a population to look for a very specific behavior, and it did end up with a with a product that seemed very similar to a dog in the curled tail. All the things that the game references in terms of the curled tail, the floppy ears, the barking,
Brian  35:54  and then the spotted coat, the change in coat patterning. Exactly,
Angela  35:58  the change in coat colors and the patterning and the generalized behavior that seems very dog-like.
Brian  36:03  If they had done the experiment with wolves instead of foxes, admittedly harder to do. But what do you think it would have ended up like? Would we have ended up with the second domestication event of of a dog like animal?
Speaker 1  36:17  I mean, it's a good question. You'd have to go through a lot of wolves the way that they went through a lot a lot of foxes you have to go through a lot of wolves. There are there are a number of groups now who are working on canine cognition and are raising, for example, wolves and dogs together to see if you raise a wolf pup within a pack of dogs, does that change its behavior? How early would you have to get a wolf? Do you have to get it right at the point of birth to affect its behavior, or can you get a wolf that you get right at the point of birth? Raised in a house just like a dog, and still it just ends up a wolf. Yeah, this
Brian  36:56  is really funny to me because it's the analogy of the humans raised by wolves. We've got the wolves raised by humans or dogs. Like, and there's there's still there's still exactly.
Speaker 1  37:07  I think that the farm fox experiment. Some of the criticisms of it are actually interesting when you think about the dog domestication side and the wolf population that it came from. The criticism of the farm fox experiment of it already being a controlled population of fur foxes, and maybe there was already some preconceived notion of how that stock population was conceived originally. Maybe very similar to dogs. As I was saying before, we have this kind of ghost wolf stock population that we've yet to find that we know is the ancestral kind of domesticated stock population of of domesticated dogs. We've never found these wolves. We assume that they're extinct because they are not they're not directly related to any modern wolf populations, and it may be that a very small potentially Siberian population of wolves that had something special about it, something unique about it, something that made it the population it was, gave rise to the first domesticated dogs, and that that whatever it was about that population is what allowed that to happen. And and similarly, the criticism of the farm fox experiment that it was that population of foxes that made it so easy to see these these changes within certain number of generations
Brian  38:27  because they were working with sort of a reduced specialized gene pool already
Angela  38:31  right
Brian  38:31  so when you said ghost wolf not really knowing much about how the sort of mapping works there's some sort of genotype that all dogs share but specifically no wolves have at this point. Is that kind of what that means?
Angela  38:43  So we know that all dogs come from the same
Brian  38:48  Go to heaven. Sorry,
Angela  38:49  and also go to heaven. That they all come from the same the same wolf stock population. There are our modern, historic, and ancient dogs. All dogs that we've tested genetically all come from the same stock population, so we don't have evidence of multiple domestications from different wolf wolf populations. So there are some papers I've been part of them where we thought we may have had dual domestication instances, but what we found is more likely is that we have a single population of wolves that we've yet to find ghost wolf. That those wolves led to an initial domesticated population of let's call them like
Brian  39:33  pseudo dogs, pseudo
Angela  39:35  dogs, like tamed wolf pseudo dogs, early dogs, and that those dogs most likely than with humans moved across the world in different directions, right? Some of these dogs moved into the Americas, some of these dogs moved down into the rest of Eurasia, and that those early dogs, as Jason was saying about corn, interbred with local. Wolf populations, right? So the dogs that moved into the Americas interbred with American wolves. The dogs that moved into Germany moved interbred with German dogs and Russian or Russian wolves and German wolves and and all the different wolf populations. And that that very early interbreeding is what has confused some of the genetics to make it look like maybe there were multiple domestications, but really we think that there's just one-a single domestication from a single population.
Brian  40:29  That's really cool.
Jason Wallace  40:30  So, with all these things we've been talking about in terms of the pattern of domestication, the way it happened, how it spread, how much of that is shared with other things we've domesticated other animals, so we've mentioned cats, which I think are another like self-domesticated ones because they hang they hung out around our grain storage because there were lots of rodents and we liked them for that. But it was only relatively recently we actually started truly keeping them as pets. But like cows, horses, pigs, chickens, like yes. How how much of what we've talked about is like happens in parallel with all of these other things, and how much of them is it's specific for dogs and foxes?
Brian  41:09  Because I think that's one of the key things. Is like you know what you can think of for all of those? They've all got floppy ears, and it's like isn't that weird that the chickens don't ears? Well, no floppy ears. Fine, Jason, you're right. Chickens don't some
Angela  41:21  cats. The mammals
Brian  41:23  mostly.
Angela  41:25  I'm part of team are cats domesticated, but we'll leave that for another time. But I think that yeah, you're right, Jason. That there's certainly we can imagine some of the earliest domesticates, especially the the carnivores, were in this self-domestication group of maybe it most likely wasn't intentional, especially with dogs. There, a wolf is a competitor. It's a dangerous predator. There's no obvious reason to domesticate a wolf, and so it's most likely a self-domestication event. Delicious
Brian  41:58  wolf milk.
Angela  41:59  Yeah, I mean we have some ritual ritual things popping up with wolves, but most likely it's a it's a self domestication as were cats. But we can imagine a scenario in which once people start seeing that you can domesticate an animal and and the effects of domestication, then you know the juicy auroch and the the goat that has like nice you know fur that you would like to make something out of become probably becomes more once you get to the livestock animals that it becomes more about genuine thought of the intentional domestication that they've seen the the blueprint of it with with dogs and cats, and they think, okay, we can start. and And I would imagine there are some similarities with plants, where you start kind of doing wild cultivation of things, and and you start taking in a few of the animals and corralling them, and then figuring out how we could corral more and more and more of them, and then breed them with each other, and then you move into this kind of domestication event. And once it feels almost when we see the timing of domestication of particularly livestock animal, it feels like a domino effect of once we figured out we could domesticate our prey, that it seemed a lot easier than going out and hunting and gathering on in in the environment. And so, once you domesticate one of them, then the dominoes kind of fall into place with all the other livestock animals as well.
Brian  43:31  Jason, could you give us a brief aside about the early steps of domestication? Let's just do grains.
Jason Wallace  43:37  Okay, this is not my area. I'm going off of what I remember from other sources, but my understanding is that it was again probably incidental domestication, where we were gathering grains out of the environment. Humans like things that are big, and so we tend to go for the bigger grains. We like things that stay on the stalk because that makes them easier to harvest. And as we do this, we would incidentally select for some of those, and then some of them would end up in our trash heaps, or they'd pass through our digestive system unperturbed, and they'd grow there. And so you'd have sort of populations of semi-domesticated grains growing around our centers, and then over the course of hundreds or 1000s of years, people started doing that more and more intentionally. And my understanding is there probably is a very smooth spectrum between pure hunter-gatherer. We're just going to live off what nature provides. To all right, now we're starting to manipulate things where we're going to make sure that the plants we like get planted here, or we like. This is one I've heard about Native Americans, like Native Americans, hunted deer, and they did controlled burns of the of the forest to sort of clear them out because they made them better habitat for deer and probably a bunch of other things. To, now we're going to intentionally like plant plants and be really intensely like sedentary agriculture stuff. There's a. Whole spectrum between there and that I mean, there's probably a few hard breaks where you can say, okay, this is going from not sedentary to now sedentary. But even that may be your you're sedentary for some of the year. Well, not sedentary. These are not like ancient peoples just like sitting around on their like stone tables or anything. This is them staying in one place as opposed to like following the herds around or moving with the seasons, but that there is probably a smooth transition, a smooth spectrum between all of those opportunities, and that we are simply living at the end result of many 1000s of years of that being operating, and we have inherited essentially the very far extreme of that spectrum, where we are now engineering essentially the entire planet to be for our good. We're
Speaker 1  45:45  ordering our grains on DoorDash, having them delivered to having them delivered to us
Brian  45:51  for grains. It seems like that first key trait is is the lack of shattering, where you touch a grain and just drop all its seeds. That's like almost one of the first things to go right.
Jason Wallace  46:00  I I don't know the order. I know it's a very common one for the grains. I think it's probably different if you go to like fruits and stuff. Oh sure, it
Brian  46:08  is. We
Jason Wallace  46:08  do like things that kind of stay on the plant until we're ready to get rid of them, instead of them falling off on their own.
Brian  46:14  Another big one that's been broken many times is seed dormancy. You want them to grow when you plant them. Yeah.
Jason Wallace  46:20  So the thing being that in nature, a plant usually doesn't want all of its seeds to grow immediately because if next year is a bad year, then all of your offspring die. So a lot of times the seeds will generate germinate kind of randomly over the next few 5, 10, 20 years or something. And so what humans have selected for is that if we plant a seed, we want the plant to grow, and so we have selected our plants so that they no longer are dormant for extended periods of time. And there are some crops that are only partially domesticated around the world. Like they, most of our industrialized listeners won't know about them because they don't tend to be produced in large quantities and sold supermarkets. But there's a bunch of them. Like teff is one from Ethiopia. People might hear of it's used in injera, which is the traditional bread. It's only really partially domesticated. It still shatters a bunch. Like a bunch of it falls down. It the plants fall over. There are people working to improve its qualities. But so like as with animals, with plants, we have a large spectrum from purely wild to corn is probably the epitome of 100% domestic because it can't survive without us at this point.
Angela  47:28  Yeah,
Jason Wallace  47:28  and you can argue that our current society can't survive particularly well without corn at this point. Yeah,
Angela  47:34  agree. We have the same in dogs. I mean, we move from a single single heat cycle in wolves to having multiple heat cycles in dogs because we want to increase reproduction and get more puppies faster, and so we have those kind of similar mirroring effects of of what domestication does to plants and animals. Yeah,
Jason Wallace  47:54  I mean, so ultimately, all we're doing is when we domesticate things, we're breeding for convenience. It's it's just whatever makes it more convenient for us. Yes. Yeah.
Angela  48:02  Exactly. And if it's not convenient, we cull and start again. We we try again with a different individual or different population, which I think maybe goes back to the farm fox experiment, the game of you know where you where you cull out, and this is not in your f2, and we're gonna not choose that to move on.
Brian  48:22  You have been on podcasts before because you've been giving us the perfect transitions to this. So thank you for bringing it back to the game. Let's let's jump into our nitpick corner, Jason. Do you have any nitpicks about the game?
Jason Wallace  48:34  Honestly, just the biggest one is that that background is busy. Like I wish the background were a little cleaner because it was hard spotting, especially because some of the card decks have the same back as the background they're placed on, so they kind of blend in, and so I would like more visual differentiation there.
Brian  48:56  So Jason's suggestion is just a 60% opacity filter over everything except the functional parts of the board,
Jason Wallace  49:02  something like that. And if we could somehow streamline this setup, that would be nice because that is a very intimidating setup.
Brian  49:08  Probably, you know what? I'll bet you one of those like box inserts that you can get now, but 3d printed that kind of keeps everything laid out, and you just take it out of the box and you set it down, and you're ready to go. Or like, hey, all those cards that you need for the solo mode that I'm not going to play anyway. I'm just going to take those out and set those fully aside, or something like that. So my nitpick, I already mentioned it, is the fact that the game and the experiment are actually opposite to one another.
Angela  49:30  Right
Brian  49:31  experiment was to select for friendly foxes and nothing else. Right? You get all the other stuff as a consequence, and in the game, you're doing the exact opposite. You select for all the other traits, and then you get a friendly fox.
Angela  49:43  Probably wouldn't be as exciting if you rolled one dice.
Brian  49:45  No, absolutely not, and I'm sure that's what it is. But basically, the way they sort of abstract this, the metaphor that we're doing is the friendly dice can account for any of the other traits. So this is their sort of like nod to that Representation, but fundamentally, the game is the exact opposite of the actual experiment.
Jason Wallace  50:05  Yeah, and the the friendly dice are basically the wild dice. You always start with one, but you can unlock with upgrades additional dice of that type to roll, which you can argue is kind of like breeding for friendliness explicitly. It's not the same way you're breeding for everything else because none of the foxes have an actual friendliness trait, but it's it's in that space.
Brian  50:26  Angela, I don't you didn't play the game right, so I mean,
Angela  50:29  I watched it. I watched the videos about online, and it was really interesting. I thought the same thing you did. It's actually flipped, but it does some have some of you know those elements of of the randomness of the various phenotypes, like popping up and and choosing what you keep. In the experiment, they would have chosen purely based on behavior. But I bet towards when we're getting to the end of the experiment timeline, we're starting to choose. You know, if the the investor wants a beautiful blue fox, now we're so now we're selecting for color and ears and and tails. So eventually we get there. But I do think it's you know we've all done the kind of Punnett square in school. But I do think it's a really unique idea to try to to have people think about genetic selection and the randomness of of genetic selection, sometimes it would be fun if there was a dice that was like bites you versus sniffs you versus licks you, and you get to select on on behavior in that way. But but yeah,
Brian  51:35  it's like crocodile mile. You have to actually like you know you have to yeah the game bites your hand. Yeah,
Jason Wallace  51:42  yeah, that's Crocodile Dentist. We had that one. We have
Angela  51:45  it. We have it. We play it all the time. Yep.
Jason Wallace  51:47  Yeah, I thought of another one, Brian, but this is not a flaw in the game. This is just that the the whims of chance were against us when we played. We had this weird alternation of generations. Oh yeah. In one round, we only ever bred males, males and
Brian  51:59  females, and like
Jason Wallace  52:01  it's hard to get ahead when every round you only breed males or you only breed females because that means you have to use the default deck for the other half which is not quite good. So we just we couldn't make much progress because like we had a bunch of pups and they were all males or they were all females. Like, well, this is not helpful.
Brian  52:16  Presumably, that's something where with more players that becomes functionally impossible, right? To only get males or females.
Angela  52:22  Yeah, could be interesting to see what the details are of that in the actual experiment. I don't know if there was like a preference of did you end up having and in certain generations more males versus females who became docile quicker or aggressive.
Brian  52:39  Oh yeah, held on
Angela  52:40  to aggressiveness for longer. Were were males, for example, aggressive into generations much more than females. I don't know the data on that, but it would be interesting.
Brian  52:50  I know they started with a ratio of more females to males. I don't know if they work to then maintain that or not. That's interesting. That didn't come up in the little bit that I read about this. I have no idea. One thing I can say about the fox experiment, the game is that has ruined the SEO for the actual fox experiment. If you Google the fox experiment at this point, it's all pictures of the game and like you know nothing of actual foxes at this point.
Angela  53:13  It'll just be buy a $10,000 fox or play play the fox experiment game.
Brian  53:20  Okay, why don't we jump into grades, Angela? I assume you're recusing yourself from a grading process for this game. Yes, I will.
Angela  53:27  I will defer to the experts.
Brian  53:29  Okay. All right. Jason, would you like to go first? Let's get your science grade and your fun grade.
Jason Wallace  53:34  Okay. So the fun grade on this, I'm gonna go probably about B, B plus range. Like this is a game I don't mind playing, but it's not one I seek out. It just doesn't quite scratch the itch I'm going for when I play a game, and I think it's because there's a lot of things going on, but I feel like there's not a lot that I can like exert my choice to influence the way things go, other than I choose what I'm drafting, which is an important but kind of minor part of the game. I also do choose my upgrades, but a lot of those see like inevitable as like race to the upgrades as fast as I can get them. So, for science, I did not do as much research as you did on the actual Fox experiment. I want to specifically call out that I'm not going to grade it on the fact that the experiment was different from the way the game is because I want to grade on on the science shown in the game. I'm probably going to give it B plus A minus range. So I think again, getting something that actually has a little bit of the randomness of genetics that it's not inevitable that you will get something better if you put two good parents together. That's fair. I think is good. The fact that you are talking about hey all these things get kind of dragged along with the temperament, I think is a useful thing to bring about, and just publicizing this relatively obscure, at least among people who are not like canine domestication experts, relatively obscure experiment. Think would be good, so I put it kind of B plus A minus range. I don't think there is a ton of science in there. It's not like I mean I feel I feel justified in making the comparison to Wingspan in this case. Wingspan has deep science.
Brian  55:14  Look, even if it's not an Elizabeth Hargrave game, we always compare it to Wingspan. We have to.
Jason Wallace  55:19  Yes. Well, I feel extra justified this time. It's like Wingspan has deep scientific information. It is baked into all the cards, multiple layers of it that you can engage with. There's just not that much depth in this one, so that's why I'm going to give it that B plus A minus.
Brian  55:33  Okay, I am going to go B on fun. I think we're about the same on this. I think it's an interesting game. I think at this point, it's just it's gonna come out a little lower for me than genotype. If I want to play a genetics game, well, first of all, I like plants, but also I want to use the Punnett squares. I think that's really fun and cool. And this vibe-based genetics just isn't quite doing it for me. On the science, I am gonna give it a B, and I legitimately I'm giving it a B because the game is opposite to the experiment. It just is like that's okay. Like I don't have a problem with it. But if we're talking about representation of the science in the game, you're selecting for everything but friendliness, which is fundamentally the opposite of the game. But a fantastic scientific story, right? The story of this and sort of raising awareness of this. I mean, like you said, National Geographic. Like this is this is something that captures the imagination very well. So I'm glad it's out there. But again, the the science is a little inverted. So for that reason, I'm just going to knock it down to a B.
Jason Wallace  56:30  So Angela, not grading, but do you have any final thoughts about this game, about what it portrays, about your field of research, or just things you want people to take away from it?
Speaker 1  56:40  Any time we're talking about dog domestication and the public science sphere, I'm excited. You know, dogs aren't something hard to get the public involved in, engaged with. But I talk a lot about dog genetics, and it's not always clear to a lot of people what what it is we're talking about. And I think, like you said, Jason, trying to help people understand the absolute randomness sometimes of genetics and the the results of of what you get. Trying to help someone tend enough, trying to understand genetics is is great. Any game that can do that. I haven't played genotype, so maybe I need to get on genotype. But I think that's exciting. I think to address Brian's point, die that referenced the things of like biting and sniffing and tail wagging when you get closer to the cage might have been better roles. And then to build on what you're saying, Jason, there's nothing more after that. Maybe there could have been a second layer that then builds in the phenotypic changes that you see, and somehow creates a co-play between those two sets of variables. That would have been that would have been interesting. Maybe there's an add-on pack because what this
Jason Wallace  57:53  game needs is more complication. More complicated. We need more complicated. We need more. How will people
Speaker 1  57:57  feel like they're scientists if they don't have an intensive scientific design before they get to play.
Jason Wallace  58:04  So I guess last question, Angela: If you had $10,000, would you get a domestic fox? Ooh,
Speaker 1  58:13  you know, I think I would get a lot of judgment from the dog community if I did. But I mean, it is tempting, right,
Brian  58:23  Mmm
Angela  58:23  have a little a little fox hanging out. It feels like the best of both worlds. If you can't decide if you're a cat person or a dog person, you get a fox, and it feels like a very middle ground. And anything for science. If we if we're saying that luxurious $10,000 foxes are funding scientific experiments. We're in a research science funding crush right now, so you got to do what you got to do to get your science funding. So I'm buying a fox.
Brian  58:52  Okay, Angela, thank you so much for taking the time to come on to talk to our listeners, to talk to us. It's just been great. Do you use social media, or is there anywhere you'd like our listeners to sort of follow your research?
Speaker 1  59:04  I I use LinkedIn. Okay, and that's about it. So that's why you're not the only person we know who does that. Jason likes to say that's basically me.
Brian  59:13  Don't do social media.
Speaker 1  59:14  I would like to believe one day I will be just like one day I will be a podcast listener that I will also be a social media user, but I'm still getting there. Maybe in my retirement, I will just be a person who just like has a dog podcast, and then that's what I'll do. But not yet, no.
Brian  59:31  Okay. Well, with that, I think we're going to cut that here, listeners. Thank you for tuning in. Hope you have a great month and great games. And as always, have fun playing Dice with the universe. See ya. This has been the Gaming with Science podcast. Copyright 2026. Listeners are free to reuse this recording for any non-commercial purpose as long as credit is given to Gaming with Science. This podcast is produced with support from the University of Georgia. All opinions are those of the hosts and do not imply endorsement by the sponsors. If you wish to purchase any of the games that we talked. We encourage you to do so through your friendly local game store. Thank you, and have fun playing Dice with the Universe.
Transcribed by https://otter.ai
 

#EndangeredRescue #EndangeredSpecies #PuzzleGame #GenCon #BoardGames #Science
Summary
In this special just-in-time-for-GenCon bonus episode, we sit down with Marc Specter and Ace Ellett to talk about their "Endangered Rescue" puzzle game series, including both the Lemur Leaf Frog (which we played) and Chambered Nautilus (which is coming out as this drops). We talk about this series's origins as the hybrid of a traditional board game and one person's annual holiday gift, the challenges of meshing puzzles and science, and the joys of cephalopods. So sit back, contemplate your favorite endangered species, and enjoy this bonus episode of Gaming with Science.
Timestamps
00:00 Introductions
03:25 What is Endangered Rescue?
07:06 Penguins, Frogs, and Devils, oh my!
12:13 Mixing science and puzzle game
18:15 Talking with the experts
23:02 Game recommendations
25:58 Wrap-up
Links
Endangered Rescue (part of the Endangered World series)
Grand Gamers Guild website and facebook page
Bluefish games 
Science Friday and Cephalapod Week
Dorian Noel (science illustrator)
Game recommendations: Scythe, Gorinto, & Bier Pioniere  (Board Game Geek)
Find our socials at https://www.gamingwithscience.net 
This episode of Gaming with Science™ was produced with the help of the University of Georgia and is distributed under a Creative Commons Attribution-Noncommercial (CC BY-NC 4.0) license.
Full Transcript
(Some platforms truncate the transcript due to length restrictions. If so, you can always find the full transcript on https://www.gamingwithscience.net/ )
Jason Wallace  0:06  Hello and welcome to the Gaming with Science podcast, where we talk about the science behind some of your favorite games.
Brian  0:11  Today, we're going to talk about the Endangered Rescue series by Grand Gamers Guild. Hey, welcome back to Gaming with Science. We're doing a creator interview today. This is Brian,
Jason Wallace  0:23  and this is Jason. Soundy little froggy because I either threw my voice out yesterday giving an outdoor lecture, or I have finally developed an allergy to corn pollen, and I'm not sure which it is.
Brian  0:31  Anyway, we are joined by two guests today. Mark, why don't you go ahead and introduce yourself?
Marc  0:35  Sure, I'm Marc Specter of Grand Gamers Guild. I consider myself the largest of the small indie publishers, we are entering into our 10th year of publication. If you can believe it, I started out in 2016 with one little title, and these days I'm kind of amazed. And I'm juggling about 10 titles at a time in various stages of development, and I work with amazing creators, both designers as well as artists, I fire emails and build relationships around the world, and the journey's not even close to over yet.
Brian  1:08  So I was at Origins, and I ran into Marc and he introduced a game to me that I thought would be interesting for us to talk about. So we've got somebody else with us today, the designer or one of the designers of that game. This is Ace Ellett.
Ace  1:20  Yeah, hi. My name is Ace. I'm like you said, one of the designers of the whole Endangered Rescue series right now. My wife Anna is the other designer. Been playing escape rooms together for about 10 years now, and that's kind of where we come from with the background of all this. But designing tabletop games for the last six or seven years since about 2019, we do some of our own designs, but through a friend, we got paired up with Marc about two or three years ago now.
Brian  1:45  So, Ace, I want to ask you a question because I've been curious about this. Were escape rooms really a thing before the Saw movie franchise?
Ace  1:54  They were certainly a thing. I think in Asia is is most commonly the agreed upon a location of where it started, but it would have been early 2000s, I believe, and I think that saw movie probably would have been like 2004, 2005 here in the states. So we we really saw a a huge surge of that, and especially during pandemic time later, to get a little even further ahead of that, a lot of games being played at home, being played digitally or online, I don't have to go to to a location and have them lock me in a room in order to really experience the the fun, the sense of just awe when it comes to solving all these puzzles  and getting that hit of like feel goods from realizing how smart you are, 
Jason Wallace  2:43  is calling it an escape room game? Is that basically branding over like a puzzle game, or is there a separate genre of puzzle games?
Ace  2:51  That's a very good question. We say escape room games. Anne and I run Bluefish Games outside of working with Marc, which is sort of a separate puzzle game endeavor. We would say puzzle games when we describe what we do. But the public at large, they're usually more familiar with escape room games. So, in the sense that you're taking, you know, somewhere between half an hour to some games last 3, 4, 5, hours, and you're you're kind of working through a narrative and getting to an end where you have an answer, yes, it's an escape room because that's going to follow that same path.
Brian  3:25  Okay, so tell us about the Endangered Rescue series. 
Marc  3:28  Ah, sure. So I'll I'll start if you're okay with that, Ace. Endangered Rescue is kind of the baby that came out of Holiday Hijinks and Endangered. So back about five years ago, I got wind that Jonathan Chaffer was making a small escape room game. Now Jonathan has an annual tradition of building an accessible, small, portable, inexpensive game that he can send to friends and family, gamers and non-gamers to as as a cute little Christmas gift, and he's done all sorts of different things for I want to say at least a decade. But he could give you the specifics.
Jason Wallace  4:10  It is like the world's most awesome Christmas card.
Marc  4:13  Yeah, seriously, literally. Sometimes it is on a card or or postcard, and so I got wind. He did an interview that he was doing a Christmas-themed mini escape room game. I reached out to him and I said, "Jonathan, we got to do this thing. Let's make this a real published game. And it was great. And then I said, "Well, can you do it again? And can you do it again? And now we've done that 16 times. I also do a game with another designer called Endangered, it's a cooperative game about saving endangered species, about convincing the United Nations that an animal is worth saving. One of the chief variations comes in the animal scenarios. While of course every board game is an abstract of reality, we work really hard. Or let me just say Joe works really hard to make sure that any every animal feels different, and that they are as reflective on the board as they possibly can be of the real life animal. The primary scenario in endangered is the tiger scenario. It's the first one, and in the real world, tigers are territorial, and so after they mate, they split up. And so in the game, we represented that that after tigers make a baby, they split up. The mom and the dad-they're just bits. They're not actual mom and dad pieces. And the baby all end up in separate areas, which creates other confounding things as to progressing your success in the game. So now, after we had a very successful set of what we called holiday hijinks, but now we've backed up and to have a larger title called 18 Escape, and we had Endangered going really well and successfully, I think I just kind of was looking at one day what we could possibly do with the system, and I loved the idea that we might be able to build an animal rescue adventure around those two things, and I talked to Jonathan, and so he went to put out feelers, basically introduced them to me, and I pitched Ace and  Anna on what I wanted to see happen, and we were off to the races. And the very first endangered rescue was Galapagos penguin, and then that was followed by the Lemur Leaf Frog, and now we have two more coming. One is Tasmanian Devil, which was done hand in hand with the Endangered Australia expansion. The newest one will be will be Chambered Nautilus, which is done in partnership with Science Friday, a radio show turned podcast that has been on the air for forever. Gosh, I want to say at least three decades, doing science, entertainment, and reporting, and in support of their annual Cephalopod Week.
Brian  6:54  So the Endangered Rescue 18 Card Escape series is part of the Endangered Expanded Universe, the the Endangered Cinematic Universe. Yes,
Marc  7:01  there you go. There you go. Like I said, it's like endangered. It's like endangered. And 18 escape had a baby.
Brian  7:06  How have you chosen which animals to focus on? You said penguins, lemur leaf frogs. Tasmanian devils are really cool. We wait. We didn't do our interesting science fact because this isn't a normal episode. But the the contagious facial cancer of the Tasmanian devil, is that part of the game?
Ace  7:24  Yes, it is.
Marc  7:25  When I the little I know about Tasmanian devils, that's one of the chief threats to their existence. So, I mean, I don't really inform what Ace and Anna do in terms of content. I trust them implicitly to research and vet the substance, along with the consultation of our subject matter experts. Hope to hope hope to enjoy that in the not too distant future.
Brian  7:45  Ace, are you the are you and Anna? Have you been the ones who've decided which animals to focus on, and how have you chosen?
Ace  7:50  Yeah, a lot of the times we will do research across several different animals. We've got some sort of broad requirements that we use. Usually, we use the IUCN list to To look at endangered species, we we try and make sure that they're classified into all the way into endangered, and I think the Nautilus actually is the the first one who might be slightly on the edge of that, just because of that group trying to actually get enough of a sense of the population of the Nautilus to be able to say they are endangered. In in the past, the animals that we've looked at, we've looked for animals that, first of all, that aren't in the endangered board game because we we want to branch out from that a little bit, but also we're trying to to find animals that are both interesting to people that that are going to capture you you know your imagination, but also that we can connect to in some way, and that we can talk about what is the threat to them. What what are they actually endangered from? So that's something that we look at because the endangered board game has this notion of roles. In the endangered rescue games, we've taken inspiration for the theme of the game and the narrative, the story; those are coming from not only the roles in the endangered board game, but cards in the endangered board game. So, in the case of the penguins, you're actually a a wildlife television show host, and you're on location creating a television show, and you kind of branch off from that into this adventure that you go on. The goal of the game actually ends up being, you know, get your show aired, get it to the production facility. There's a card in Endangered that says produce the season two of Wild World, which is the name of the show. So we kind of start from there. We look for what could match up, and hopefully tie it all back together. And we actually talk with Joe frequently as we go through these, and he has a lot of good ideas for, you know, animals that he's thinking about in the future or that he's looked at, and he's like, not not quite good for the board game, but would be interesting. So kind of a big mish-mash of all of that.
Marc  10:01  You know, we as gamers we crave novelty. I mean, that's why the cult of the new is a thing. And one of the things I've asked Ace and Anna to do is have a breadth and depth of creatures. We want different species. We want different environments. And that's why we've gone from a an aquatic bird to an amphibian to a mammal to a cephalopod
Brian  10:21  to a weird mammal, a a carnivorous marsupial, and now arguably one of the weirdest of the cephalopods. Yes,
Marc  10:28  yeah. I just think you know. I think we focused on chamber nautilus esthetically. To Ace's point, it's important to have an animal that it will captivate people, and I think the chambered nautilus is just so amazing to look at that you look at it, you kind of just are in awe of the the visual presentation.
Brian  10:46  I mean, shelled cephalopods used to be like most of the cephalopods.
Jason Wallace  10:50  Ammonites ruled the ocean for a long time.
Brian  10:52  Ammonites and orthicons, the ones with a long extended, you can find fossils of them all the time. But like now, we've just got the chainbered nautilus. How did this partnership with Science Friday developed, so this seems like a wonderful thing where you can correlate the game to their Cephalopod Week, which I guess is their answer to Shark Week. Yes,
Marc  11:09  yeah, sure. I have been a fan and listener to Science Friday for at least 15 years, and of course, every year I hear the Cephalopod Week. Well, one day listening to an episode, they just rattled out a phone number. I said, "You know what? To heck with it. I'm giving them a call. I left a voicemail that said something like, "Hey, my name is Marc Specter. I'm a board game publisher, and I have an idea that I'd really like to pitch to you for Cephalopod Week. And it wasn't really very long, quite frankly, until they called me back, and they really loved what I what I had to offer. Of course, we are giving a royalty back to Science Friday as thanks for their partnership, as thanks for their co-branding, and in support of Cephalopod Week. Yeah, it's just been a really wonderful relationship. Just that came out of my my desire to do something for an organization that I feel has done so much for me. They've just educated and entertained me for so long, the ability to give back to them in a way that is both monetary and fun and tangible really is kind of a tentpole event in both my professional and my personal life.
Jason Wallace  12:13  We played the lemur leaf frog. How challenging is it to try to blend the science and the puzzle? Because I know I definitely felt like sometimes it felt like they weren't mixing in the game. Like literally, the the answer cards would have the science fact on the top, and then like the puzzle next step on the bottom. We only played the one game, so I don't know what the other ones are like. But how easy is it to try to get those to mesh organically, or is it that you really are taking? We're gonna take a bunch of science facts, and we're going to take a puzzle game, and we're going to kind of glue the two of them together and make it work as well as we can.
Ace  12:47  Yeah, that's a really good question. And the lemur leaf frog game is actually is furthest in the direction of I don't want to say like far away from the the frog itself, but kind of in that game, the story is that you are running a fair or you know a community event. They're selling food. They're you know presumably going to put on some lectures or to engage the community. When you hear someone talk about conservation and imagine how you can impact conservation, I think people have this notion of like you can only do that if you're going out in the wild and like crawling through plants and you know actually being with these animals and that's one of the things that we wanted to really emphasize was it is anyone it can be any of us and doing things is really where where it starts and those things can be really small. Those things can be, you know, putting on this local town fair. It could be making sure that you know, just handing out leaflets, that sort of thing. But really, taking any sort of action at all is is I think the the foundation of of these these stories about conservation in in the Lemur Leaf Frog game, we are talking about your journey through what is a little bit of administrative process. But throughout all of these games, like you said, we want to make sure that you might do a task that's like figure out where these tickets go, figure out how to get into the cash box in order to get get the tickets that you need to give to people. You're using puzzle solving skills during that time, but you're also going to pick up a couple of facts, sort of like sneakily, by reading what's happening in the game and see just being immersed near those people and near that subject matter. So in all the games, what we hope is that they play this fun game, and along the way they're like, "Oh, that's interesting. Like I didn't know that thing, and then later, you know, it's something that that that can it's an amount of information that can stick with them, and they can really they can carry forward, not to to be. Mean to the subject, but that some people will find hard to grasp or less interesting. So, we want to push the the puzzling and that knowledge of science topics together. 
Jason Wallace  15:12  Brian, you did the puzzle that involved actually looking up the tree frog facts, and I think we were working together on the one that involved looking up with all these things provided as part of the game, like the list of various endangered or threatened animals in its same habitat, 
Ace  15:25  and we we want to give you, like I said, not overwhelm you. Yes, the information that we give you is almost always used. It's information that we've gone through, what we think are the most interesting bits of this situation, and we've then compiled that and given that to the the person who's playing.
Brian  15:43  You've got like Chekhov's clues. It's like, well, they wouldn't have put this information here if it wasn't important.
Ace  15:47  Yeah, exactly. Like we're right there next to you. We're excited that that you're playing. We're hoping that you're having a good time. If you don't feel smart at least once through the game, like that's on us. That that's our failure. But even more so than that, if you feel stupid at any point, that is that a huge failure. That's like a stop for us. Like, let's go back and redesign whatever you did. So there's lots of ways of signposting information. There's lots of small visual clues. Anna is our designer. She's great at putting something on a card, and you don't even know it, but you're like, I see this shape here, and that's going to trigger something in my head.
Brian  16:29  I I do like this idea, something you're emphasizing of incidental learning. I think all of the best games with science aspects in them sort of encourage that. There's also this idea. I was just listening to an interview by Peter Hayward. You're going to use it to solve the puzzle. It's also probably going to stick with you. I learned things about the lemur leaf frog that I didn't know.
Jason Wallace  16:47  So, who's your target audience for this? Is it puzzle gamers? Is it people more in the nature conservancy area playing it? This actually felt like this would work really well as like a K through middle school educational tool way of making learning some things about endangered animals slightly more fun by wrapping it up in a bit of a puzzle game. Like, who are you targeting with this?
Brian  17:11  Some of those puzzles might be kind of hard, though.
Jason Wallace  17:14  Okay, maybe not K, but middle school, middle school. Yeah,
Marc  17:17  right. I'll say that our target audience is all of those, and in fact, one of the exciting things about the relationship with Science Friday is that they have their outreach programs, which may in fact help us get the chambered Nautilus into middle and high schools, where they can play it as a classroom. In terms of what my organic reach is, you know, we're going to be in your local game store, and we're also going to be at your board game convention. So we are mostly hitting gamers, and some of those are puzzle gamers already, and some of those are people we have turned into puzzle gamers because of how accessible our games are. Going back to what Ace said, we want people to have a good time. We want to tell fun stories, and we don't want you to walk away feeling bad. We have a graduated hint system, so you never get stuck, and that you can continue and complete the adventure, unlike some other systems, in a way that will get you there.
Brian  18:15  So, Ace, let me ask you: How did you do the research on the animals for the game, and how did you find your science consultants for the different animals.
Ace  18:23  Yeah, those are kind of the same answer for us. So, like I said, we start with probably five different animals that we're considering, and Anne and I will usually split those up and look into can we find a hook? What what are we going to use as the story for the game? As specifically talking about what someone can do to help. So that that's something that we look for in a lot of these animals. Is this is the problem? I want to be able to quantify what these animals are going up against, and then maybe give a suggestion for someone how how someone might be able to help. Usually, once we have an animal in mind, a lot of it is just kind of exploring, just you know, Google, find different resources, find trusted sources who, and find sources that agree with each other. In several of these cases, we've been lucky enough, especially through our connection with Marc, he's been able to find often the expert that we are reading the papers from. So nice. In the case of the Nautilus, we went and we did some research, and we found there seemed to be one particular scientist. I'm I'm hoping I'm not saying his name wrong. We haven't actually met in person, but Dr. Barord, a PhD who works with the Nautilus, we were using a lot of his source of his material, his lectures, videos, articles. We were using that as source material to inform our puzzle design. Talking with Marc about designing this, he said, "Hey, I've I've reached out to this person", and it turned out to be the same guy. We're like, "This is great. This is you know this is the expert that we've been getting our information from". Building on that. Connection has been great. We've been able to do that, I think, in either three or all four of our games so far. It just happened to line up, or like we've identified someone who is the expert, and then we approach them, and they have always been just the greatest people to be able to say like you can tell that they're truly interested in conservation, in preserving these animals and helping, and and they've been willing to get on board and start talking about correcting the facts that Anna and I find, and helping say, you know, what is the experience like out in the field? What can people do to help? It's just a lot of really good concrete information.
Marc  20:39  Yeah, you know they're all busy experts, but we find that if if they do have the time, they're really excited about the opportunity to see their their the animal that they're passionate about realized in a game. Been very gratifying. Also, what's been really great is that Ace and Anna create this game walkthrough that gives the the subject matter expert something quite tangible to hold on to and to provide correction with, but even more than that, they've also provided us critical feedback on our visual presentation. We have a nature artist, Dorian Noel, who does you know animal scientific illustration. But I mean, even one guy can't know the ins and outs of every animal. Let's use the chambered nautilus as an example. Dr. Barord gave us some integral feedback, like there's some sort of a valve on the guess what you'd call the face of a chamber nautilus that Dorian had neglected to illustrate. He you know he pointed out right away, hey, you're missing this thing, and Dorian said, "Okay, we'll get it in there. And so there were about three passes until we were satisfied with our cover presentation. 
Brian  21:48  A lot of experts are always excited to talk about their work, and that someone wants to hear about their work. And yeah, you'll find biologists do fall in love with their subject matter. I know Jason does love his corn. If you find somebody who studies leeches, they love leeches. Oh, they'll tell you everything that they know about leeches. But it's just yeah, we're just weird that way. I'm gonna throw you guys a question. I'm curious to hear what you think. What is your opinion on educational content in games? Because I have talked to quite a few people, and there's a lot of reluctance to ever attach the word educational to anything that you're doing in the game space.
Marc  22:27  Well, I'll begin by saying that everything I do is game first. I mean, we're not going to wildly misrepresent something for the sake of a game, as I indicated earlier. Sometimes things need to be abstracted out in order to make them playable, but you know we are a game-first company who values the integrity of the underlying information, and so we've always gotten some kind of a subject matter expert on board from endangered to endangered rescue to vet the content and make sure that we are being as accurately representative as we can be. 
Brian  23:02  The one other thing that I wanted to do, we try to do this for everybody who comes on at this point, is what is a favorite game of yours?
Marc  23:09  So, are you asking just generally a game I favor, or a favorite game that I've literally made?
Jason Wallace  23:14  A game that you enjoy playing in your free time when you want to do leisure, not work.
Brian  23:19  I don't know. I'm actually fine with both. 
Marc  23:21  Sometimes they could be one and the same. Ace, I'm going to let you go first on this one.
Ace  23:26  Sure. I have kind of polled Anna. I was definitely the one who was more on the board game side, getting started in our in developing Bluefish games. I've kind of pulled her towards more of the strategy games. One of the ones that I'm trying to get her to play more often with me right now is Scythe. One of the ones that she's been willing to play more recently has been SETI. It's been really cool to to see. I don't know that I'd call either, especially Scythe, but SETI more sort of an educationally adjacent game. Or 
Jason Wallace  24:00  we have an episode coming out on it later this season. We do.
Ace  24:03  Oh, cool. Yeah, anything, anything that has lots of different, you know, levers to pull and that sort of thing is something that I'm I naturally gravitate to. But I think, like Mark said earlier, like fun first is the most important thing. So lots of different situations, playing lots of games. I think the the important part is just being able to hang out with some friends and and pull those levers together.
Brian  24:29  If the game's not fun, no one's going to play it. That's just It
Ace  24:32  yeah. 
Brian  24:32  doesn't matter how much good educational content in there if it's not enjoyable to play. There's really no point in making it. Right.
Ace  24:39  Yep. Yep.
Brian  24:40  All right, Mark. You had either one or two answers, right?
Marc  24:43  Yeah, sure. So I will. I'll give a self-serving answer and a and a non-self-serving answer. My own game that I always enjoy and I've been spending a lot of time with lately is called Gorinto. It's an abstract engine builder that it just it is extremely. Gratifying, not just to play myself, but when I have the opportunity, which is very frequently, to teach other people, and it's a game I can explain, and you can totally understand within about five minutes. And watching light bulb go on for people never gets old. I mean, it is the game that when I am at a convention showing it off, it is the game that other people will walk by and just shout at people just by that game because because they love it and they're passionate about it. Another game that ah that's not self serving author out is called Bier Pioniere, and I cannot remember the designer and I cannot remember the publisher, but it's a small German publisher. It is just a crunchy game about brewing beer, and it's just really well done. I mean, doesn't hurt that I love beer. Just a fun abstraction of the process of building your little beer empire. It's if you like heavier euros, I wouldn't call it a heavy euro. I'd call it heavier. Seek it out and give it a play.
Brian  25:58  Will there be a Science Friday short an episode a podcast about Chambered Nautilus?
Marc  26:04  I know that they will be promoting it before and during Cephalopod Week. Whether there will be an episode about our game specifically is something that I'm not aware of. You know, I I would not deign to take up airtime talking about a game, although it sure would be exciting to do that. And I know that they're still plotting and planning. You know their schedule. They have a lot to coordinate to pull off something ambitious like Cephalopod Week. So we and we're just one small part of that.
Jason Wallace  26:30  Well, you don't need them to make an episode about the game. You've done it with us, and yeah, you just need them to link to us. And it'd be that's right.
Marc  26:37  Maybe they can put your episode on their feed and expose you to their millions of listeners-that might be a thing.
Brian  26:42  We will certainly point our listeners towards Cephalopod Week because that sounds really cool. I would like to listen to some episodes about cephalopods for sure.
Marc  26:49  Yeah, with no disrespect to you guys, the Science Friday podcast is some of the best entertainment I have had the joy of absorbing over ever since podcasts became a thing for me.
Brian  26:59  Where can our listeners find you or find out more about the game. Obviously, we already said we'll point people to Cephalopod Week on Science Friday.
Marc  27:05  Yeah. So as far as Grand Gamers Guild, Grand Gamers guild.com on the internet or the Grand Gamers Guild Facebook page, both will get you to the content you crave, so to speak. Every time you reach out, you're pretty much talking to me. I am Chief Everything Officer. I do everything from sweep the floors to sign the checks. With respect to endangered rescue and specifically chambered nautilus, we just put it up on the GenCon click and collect, meaning you can order with no shipping and then come and pick it up at GenCon. Or if you are not attending GenCon, you can simply place a pre-order, and as soon as we get it in our hot little hands, we will turn around and send it to you. So all of that again is at grandamersguild.com.
Brian  27:47  What about you, Ace?
Ace  27:48  Yeah, from our side, all of our endangered rescue games actually go through Grand Gamers Guild, so that's the best place to find those. You can actually get one thing that I really like that Marc does is he posts print and plays available for sale on that site. So, if you want to play, you know, right now, as long as those games are are published and are be are printed and everything, you could actually download the game and print it yourself and and play right there. If you're looking for Anna and I Bluefish games outside of that, we are at teambluefish.com. We run our own line of games, all set in what we call our Hincks universe, which is a whole other imaginary eccentric-led community. That's where where you find the bulk of our games. Although we're interested, and we try and have our hands in all different kinds of puzzle games and activities like that. So you may see us turn up in other places as well.
Brian  28:41  So at Bluefish, you have the Hincks Cinematic Universe, yes?
Ace  28:44  Yes, that's correct. We have, I think, like we produced a monthly newspaper for about two years. So if you count each of those issues as its own game, which it is kind of intended to be, there's about probably 30-ish games in that line in that universe, but if you look at sort of a bigger box, it's it's somewhere between eight and 10, probably. But definitely benefits from being in in universe and having experience from from game to game.
Brian  29:12  All right, so I think we're going to cut it there. Thanks so much, Marc and Ace, for joining us to talk about this game. It was really interesting. We haven't played puzzle games before, so this was a great introduction to it, and to get to play one that has sort of a science connection, obviously, sort of gave us a great excuse to do so. So, with that, everybody have a great month and great games,
Jason Wallace  29:30  and have fun playing dice with the universe. See ya.
Brian  29:36  This has been the Gaming with Science podcast. Copyright 2026. Listeners are free to reuse this recording for any non-commercial purpose as long as credit is given to gaming with science. This podcast is produced with support from the University of Georgia. All opinions are those of the hosts and do not imply endorsement by the sponsors. If you wish to purchase any of the games that we talked about, we encourage you to do so through your friendly local game store. Thank you, and have fun playing Dice with the Universe.
Transcribed by https://otter.ai
 

#Archaeology #AncientGames #Ur #Senet #Mehen #BoardGames #Science
Summary
We're looking deep into history today as we talk about the oldest board game with a known ruleset: the Royal Game of Ur. Joining us is Dr. Walter Crist, an archaeologist and expert in ancient games. We cover ancient dice sets, the meanings of games, centuries-old games made with graffiti, how Walter and colleagues are using AI to decipher now-lost rulesets, and why you should play some ancient games. In addition to Ur, we talk about Senet, Mehen, Hounds and Jackals, and several others, so grab your fedora and hand brush, and let uncover some of the oldest ways we have to play dice with the universe.
Timestamps
0:00 Introductions
2:04 Ancient dice and Egyptian honey
5:26 The Royal Game of Ur
9:15 Decyphering the rules
15:41 Who made the gameboards?
19:46 Why did people play these games?
23:38 What do the symbols mean?
25:29 Senet, Mehen, 20 Squares, and other games
32:35 Games in and out of civilization
36:08 Gaming archaeology in practice
39:54 Using AI to decipher ancient rules
47:36 Why YOU should play ancient games
51:00 Final grades
Links
Royal Game of Ur (Wikipedia)
Print-at-home version we used (New York Times)
Dr. Irvine Finkle versus an Influencer (YouTube)
Walter's BlueSky account and recent articles:
Deciphering which game was played on a board Book chapter in Sports and Games in the Ancient Near East (Archaeopress) 
Senet Households (Steam) 
Note: We couldn't find a primary source for King Tut's honey, but did fine this one about fossilized honey in Georgia (the country, not our home state) 
Find our socials at https://www.gamingwithscience.net 
This episode of Gaming with Science™ was produced with the help of the University of Georgia and is distributed under a Creative Commons Attribution-Noncommercial (CC BY-NC 4.0) license.
Full Transcript
(Some platforms truncate the transcript due to length restrictions. If so, you can always find the full transcript on https://www.gamingwithscience.net/  )Brian  0:06  Hello and welcome to the Gaming with Science podcast, where we talk about the science behind some of your favorite games. 
Jason Wallace  0:11  Today we'll be talking about the royal game of Ur.
Jason Wallace  0:17  All right, everyone, welcome back to Gaming with Science. This is Jason. 
Brian  0:20  This is Brian,
Jason Wallace  0:21   and today we are joined by our special guest, Dr. Walter Crist, who's going to tell us about the Royal Game of Ur and ancient games. So, Walter, can you please introduce yourself?
Walter  0:30  Yeah, hi, I'm Walter Crist. I am an archeologist working at Leiden University in the Netherlands. Basically, I study ancient games. Mostly, my area of expertise is in the Bronze Age, so around four to 3000 years ago, mostly in the Eastern Mediterranean, so like Egypt, Cyprus, Turkey, places like that in Greece. Lately, I've been studying that along with computer scientists, trying to find ways to use AI to understand ancient games a little bit better. I've been doing this for quite a long time now, and I think it's a really interesting and new way to talk about ancient lives that have kind of been ignored in the past. So I'm excited to talk about it with you guys. 
Brian  1:11  I recently got fascinated by the Bronze Age collapse, and I think just because it is such a crazy mystery.
Walter  1:18  Yeah, yeah, and I think it has some interesting effects on the ways people play games too, which I don't know. Maybe we'll talk about it here. I haven't published on it yet, though.
Jason Wallace  1:26  And do you have any favorite modern games? We'll talk about ancient games later. But do you enjoy any modern games? 
Walter  1:31  The modern games that I usually play are: I usually play video games. I mean, I do play board games, but mostly video games. My favorite game of all time is Legend of Zelda: Ocarina of Time. I love that, and I'm so excited for the the re-release and the remake that's happening later this year.
Jason Wallace  1:46  My wife is also very excited about that. Although we determined that the biggest quality of life improvement that there needs to be is the ability to turn off Navi.
Walter  1:54  Yes, I think that is also true.
Jason Wallace  1:57  For those who don't know the game, Navi is your annoying fairy companion who won't shut up?
Walter  2:01  Yep. Hey, hey! All the time.
Brian  2:04  Listen. 
Jason Wallace  2:04  All right. Well, let's go on to some of our fun science facts. So, Walter, as our guest, we'd like you to go first. What do you have to share with our audience?
Walter  2:12  So, there was some really, really cool research that came out just a couple of months ago by an archeologist working in somewhere in Colorado who did a study of objects that came from ancient sites going back 12,000 years in North America, mostly in West and Southwest North America, and found that there's a continuous tradition of making these artifacts that look like dice. He traced them back from the 19th century, from ethnographic collections, all the way back 12,000 years. So it seemed like people were using dice in the Americas for at least the past 12,000 years, and that's really the the earliest that we can see games in the ancient record. And I think that's really cool and exciting new news.
Brian  2:52  Are those like the six sided cube dice, or were they different shapes? 
Walter  2:55  No they're not. So they use binary dice. So basically, a bunch of like objects that are marked on one side, and they're usually you know different shapes, but they're marked on one side and blank on the other, or maybe marked differently on two sides. And you take a bunch of them and throw them, and based on what side lands up, it gives you a number. So it's kind of like if you like threw five coins and then you count every time there's a head that lands up, it gives you a number.
Brian  3:20  A bunch of D2s.
Walter  3:21  Exactly. Yeah.
Brian  3:23  What were they made out of? Are they are they made out of stone or bone?
Speaker 1  3:27  bone, and I think some I think may have been clay also or stone. But yeah, a lot of bone, especially.
Brian  3:33  So dice goblins went back 1000s and 1000s of years. It's a strong tradition.
Speaker 2  3:38  Yes, absolutely.
Jason Wallace  3:41  How about you, Brian? What do you got for us?
Brian  3:44  So I was looking around and I wanted to connect this to microbiology, but also to archeology. So I'm going to talk about a fact that everybody knows and isn't quite true: is that honey never spoils. So honey is really good at staying preserved. It's got low water content. It's got high pH (*correction low pH), and those are good things to keep bacteria and mold from growing also supposedly produces hydrogen peroxide. Well, it does produce hydrogen peroxide, but that was the like. Well, that can't be it because hydrogen peroxide is pretty stable, but it's not 1000s of years stable. So I think a lot of this goes back to oh, people have found edible honey in in Egyptian tombs, and it's kind of true. There were clay jars that I think were found in the tomb of Tutankhamen. Hopefully, I'm getting this right. Like again, this is one of these stories where like the facts sound almost too good to be true, so I'm trying to track it down. They did find clay jars that were marked with honey, inside they found sort of a slight caramel trace that a chemical testing then confirmed would have been edible honey. So you're not going to an Egyptian tomb, cracking open a jar, and pouring it out on your pancakes or something.
Jason Wallace  4:41  I think probably for most people's pantries, we can assume honey is going to stay relatively edible until it crystallizes. Yeah, but don't plan on putting in your like honey 5000 year time capsule and having it still be good.
Speaker 3  4:55  No and especially if you're not in Egypt, like the preservation in Egypt is very particular because. It's very hot and very dry. So if you're doing that anywhere else, it's definitely going to get weird. 
Brian  5:04  I think that was something they said too. Sealed jars in a tomb is a very different condition than your pantry.
Jason Wallace  5:10  I guess nowadays, if you really want to preserve honey that long, you're going to have to like vacuum seal it and launch it into space, and that's about the only place you'll be able to keep it that long. 
Brian  5:18  Space honey, 
Jason Wallace  5:21  you know someone would pay for that space. 
Brian  5:23  Oh yeah, for sure. People will pay for all kinds of crazy stuff.
Jason Wallace  5:26  Okay, all right. Well, let's wind this back then to ancient times. So we're going to talk about the Royal Game of Ur today. So this was one that I didn't know about until about a year ago, when someone we had over for dinner pointed me at it, and when I started looking into it, like, oh, we've got to do an episode on this. The reason we're doing the Royal Game of Ur is because it's the oldest board game with a known rule set. There are traces of it going back 4,500 years or so, back to about 2500, 2600 BC. And so you may have realized that our introduction was a little different. We didn't list a publisher. That's because there is none. This is way in the common domain
Brian  6:00  from "The Bronze Age",
Jason Wallace  6:02  yes, from our Bronze Age forbearers. But basic idea: this is a fairly simple, simple in air quotes game because I looked up one paper that had a mathematical analysis and was saying that in some respects it has as many like choice options as chess does, which seems strange for such a simple game. What the game is is it's a board. The one that we played on and that is most commonly shown is like two rectangles that are connected by a small thin bridge. There's a total of 20 squares on it, and basically, if you took a rectangle that had like three rows and eight columns, and you took out two of the columns slightly off middle, then you end up with like the two big rectangles and a little bridge connecting them, and this is the board you play on.
Brian  6:43  It kind of like reminds me just a little bit, not really, but like a hopscotch board, which maybe that's also not a reference everybody would get.
Jason Wallace  6:50  Again, we're stuck in the method of trying to describe something visually in an audio medium. So if you really want to know, look it up,
Brian  6:56  Jason. You're going to put this on the splash image for the episode, right?
Jason Wallace  6:59  Yes, there's going to be a splash. 
Brian  7:00  Well, there you go.
Jason Wallace  7:01   You do a Google search, you'll find it. This seems to be the older version of the game. I did find several articles that mentioned a more recent one, merely 1700 BCE, that was where they took the second rectangle and sort of straightened it out, so that you had a rectangle on one side where you started, and then a long thin section going off after that.
Brian  7:21  We just did our little minisodes. Is that then contemporary with Go? Seems like we've been talking about old games now because we did chess. Now Go. Now the Royal Game of Ur. We just keep going further and further back in time.
Jason Wallace  7:32  I think the oldest confirmed date on Go is about 500 BCE. Oh, I think this is still about 1000 years before that.
Walter  7:40  Yeah, so that's about right.
Jason Wallace  7:42  Yeah, Go claims the title of the oldest game that is still and has been continuously played. Anyway, the point of the Royal Game of Ur, it's a racing game. So you have a bunch of pieces that you're trying to get off the other edge of the board. You have some dice, which in the traditional one are little tetrahedrons, so little pyramids, D4s. If you're familiar with those from like role-playing games, or you can use binary dice, like Walter was talking about earlier. In fact, that's what we did when I made it up. Is I took a bunch of popsicle sticks and I painted one side white and the other side black, and those were our dice.
Brian  8:12  Those were really fun to throw, by the way. I think we need more games where we throw painted sticks.
Jason Wallace  8:16  Okay. Each time you you make a roll or a throw, then you get a certain number of moves. You move your pieces onto the board. You each have seven total. You sort of start in a safe place. You go into a contested spot where you can capture each other's pieces and then basically send them back to start. And eventually, you end up at a safe spot and you need to get off the board. The first person to get all seven of their pieces off the board wins. It's relatively simple and straightforward, and yet there's strategy to it in terms of picking, like okay, which is the best move to make, because there's different odds for how many spaces you'll be able to move, how many spaces your opponent will be able to move based on the dice rolls, and so there is strategy to it. And this is where that game complexity I mentioned comes into play, is because even though the number of possible game states is much lower than chess, the number of decision points is actually roughly on par with it.
Brian  9:02  Basically, it's like you're most likely to roll two. So, like if you're gonna move and there's another piece within two of you, you're at risk of being captured. So you got to think like, well, maybe, but maybe not. I mean, I might just risk it.
Jason Wallace  9:15  And I should say that what I'm describing here is probably the most common rule set, which is nowadays known as the Finkel rule set because of Dr. Irving Finkel at the British Museum, who published these based off of some clay tablets that were rediscovered. I don't know the full story behind this. They were originally archived like 100 years ago, and it took a while for people to realize they were talking about a game. And then he put these together, said, "Oh, these are talking about the Royal Game of Ur, and these are the rules we can infer based off what they're talking about. Being an ancient game, there's two things to keep in mind here. One, people have been speculating how to play this for a while. So just in my cursory research, I ran across at least four or five different rule sets that people speculate could have been used. And then the second thing to remember is that being an ancient game that was around for literally 1000s. Of years, people probably did play this in many, many different ways. You think of all the different ways people house rule different games today. If any of you play Magic: The Gathering, that theoretically has one rule set, and yet has dozens upon dozens of ways people play it. People will get creative in terms of how they use it. So there probably was not a single rule set people used. There were various ones. And Walter, maybe you can correct me on this. My understanding is that the Finkel rule set, the tablets he used to derive that, are actually not describing the base rules. They're actually describing a variation of rules from which he sort of back calculated a likely set of rules for the base game. Is that correct?
Walter  10:35  That's kind of the gist of what's going on there. So yeah, the rule set that he translated seemed to be describing some kind of variation on what probably was the base game, and probably the reason why they wrote it down was because it was something a little bit different. Because the base kind of game, the normal way that people play, everybody would just know, you know, learn it growing up, like we do with something like checkers, right? Most people don't learn to play checkers by reading the rules. You've learned it from somebody else, and throughout human history, this is usually the way people learn how to play games. So that's probably why those rules were written down in the first place, was because they were kind of this weird variation. And there are only like certain parts that are written down, which are probably the things that are different about it, rather than the full list of rules. He also draws from some more ethnographic parallels on similar games on boards that seem to be shaped similarly to what was originally the Royal Game of Ur, and now talking about the later version, the one with the long track that you were talking about, which we usually call 20 Squares. So he found out about a woman who was from the Jewish community in Cochin, India, that had well, he found a version of this game that was in the Israel Museum in Jerusalem that had been donated by that community to there, and a woman who remembered the rules and the board looks almost exactly like the ancient game. So he talked to her, and she taught him how to play this, and from what I can tell, he's taken those rules, which largely do coincide with what we can see from that tablet, and put them on this game board. And there are other types of games that have similar geometries. You know, where you have two entry points where you are sort of safe, and then you have a shared part where you can knock each other off with safe spaces that are very commonly played in particularly South Asia. That seem to be like an inspiration for okay, what might the rules have been for this game? Because this is what we do in archeology: is we find something, and okay, if you don't know how something works, you look to how people have used similar kinds of objects, and like how how have they done it to try to infer how something might be used?
Brian  12:46  So ethnographic that means just looking at similar things, other games, just to try to make a modern analogy. This would be like trying to infer the rules for like a trick taking game using a standard deck of cards. It's like well, it's often like this, so maybe we can backfill and say this would be a reasonable supposition?
Walter  13:04  Yeah, I mean ethnography is observing people in real life and like what they're doing in your current moment. If you're interested in how people use particular tools to farm or how they use particular tools to make textiles, you can observe people doing that and see how they use particular things, and then you can use that to infer if you find similar objects that look very similar to the ones that you've observed people using. Then you can sort of infer if you find the things that look the same. You know, you have this particular toolkit that looks the same now as it does in the past. Okay, they're probably using these tools to do that thing that we observe people doing.
Jason Wallace  13:40  Basic idea that ancient people are still people, and we tend to think along very similar lines.
Walter  13:45  Yeah, and also the idea that, like, as I was saying, like these games are transmitted from person to person from memory by teaching them verbally or by playing them. You also have sort of different kinds of expectations for what these games can be. You have a board, and you have a set of pieces, and maybe the dice. You can come up with lots of very creative ways to do that, and especially with what our expectations are for modern board game design. But that doesn't seem to be the case for traditional kinds of games that have this method of transmission. They tend to be quite light in the number of rules you have to remember, but quite elegant in the way they actually play out.
Jason Wallace  14:20  Yeah, it strikes me that the only ones that would last 1000s of years are the ones that were simple enough to transmit and yet complex enough to have good replayability and fun. Assuming that's why they were actually being played.
Brian  14:31  One of the things I enjoyed about The game of it's not "er" it's "or" right. It's more like "or"?
Walter  14:36  "Or" yeah, I think so.
Brian  14:37  Okay, is that I liked it because we could have a conversation while playing, and it actually wasn't that disruptive. I like a game that's like that, where you can play, you can do your thing, you can still be having a conversation at the same time, which I imagine is probably how this was played, right? You imagine a bunch of old men sitting down playing dominoes or something.
Walter  14:54  Yeah, I absolutely, in my research, I really try to focus on the social aspect of games, and I think that is probably the most powerful aspect of games, and why they last so long is because they have this local aspect. You have to play it with somebody else, and I think these kinds of games that sort of have this chance element. I mean, I guess there are a lot of choices that you might have to make, but you don't have to sit and ponder over it like you might with chess, right? I think that leads to the longevity of a lot of these kinds of games, where you just you can sit, you can have a beer, you can play a game, you just throw the dice and chat, and you know you don't have to concentrate for minutes at a time on what your move is going to be.
Brian  15:34  Just kind of a light game as far as the depth goes in a in a modern parlance.
Walter  15:38  And yeah, in in modern sense of things, yes.
Brian  15:41  I have one more question. Sorry, I know I'm Jason's got a whole outline, but okay. So where would you get the boards? Is was there an ancient friendly local game store? Are these manufactured by the individual who's using them?
Walter  15:54  So that's a very interesting question, and I don't think that there were game shops per se. Usually, what we've seen by observing people who play traditional games similar to this, and you know, with other game types as well, is people will just make it on the ground. So you'll just scratch it either on a pavement, or if if it's just the dirt, you can just make the design in the ground. You gather the pieces. You know, you can get stones or shells or seeds. In some places, they even use animal droppings like goat and sheep.
Brian  16:23  Oh, delightful! 
Walter  16:24  Yeah, but that's also why the dice are often binary dice because you can just get sticks and split them in half, and then you have binary dice. You just gather stuff that's around and use them to play the game. And I think most people didn't actually own game boards until fairly later in time, you know the game boards that we see, you know the early Royal Game of Ur boards that you're talking about that were found in ore were found in the Royal Cemetery, you know, made out of semi-precious stones and ivory and stuff like this. This is stuff that the wealthy has, you know, specially made for them.
Jason Wallace  16:56  These are your designer boards, basically. Like you get these nowadays, where they're like they've got metal inlays or mother of pearl, the ones that cost hundreds and hundreds of dollars, which are meant to display and be more of an expression of hey, I spent a lot of money on this rather than something that you would just pull out and play with friends.
Walter  17:12  Exactly, yeah. And the case that I like to talk about is the Tiffany and Company, you know, the famous jewelry store. I don't know if they still do, but they were at one time selling a tic-tac-toe board that was, you know, you could pay several $1,000 for
Brian  17:26  for a game that you can play with, like you know, a scrap of paper.
Walter  17:30  Exactly, it's an expression of status more than anything else.
Brian  17:34  I feel like the same thing is definitely still true with chessboards. People like their extremely elaborate chessboards when you could literally make a chessboard out of just about anything,
Walter  17:42  yeah, absolutely. And I and I mean, even some modern games may not be as much of an expression of wealth to a certain degree. It is, but you know, these games that have tons and tons of components and like are very well made and they cost hundreds of dollars for the box. It's an expression of how dedicated you are to being a gamer, at least right. The
Jason Wallace  18:03  real modern equivalent of that is all the Kickstarter upgrades, where you got the basic game, but then you can upgrade for like the nice metal bits and the ones that have like the inlay on them and all the fancy 3D printed bits instead of paper tokens and such. So
Brian  18:17  this is something that's come up before when a game has a nice feel to it when the tokens have a nice weight to it. It does add a level of satisfaction to the play. It doesn't really change the play, but it changes the player experience.
Walter  18:30  Absolutely.
Jason Wallace  18:30  Yeah. All right. So before we go on to going in depth on the archeology, I do want to do one final thing. One thing I noticed is that when people talk about this game, they oftentimes compare to like checkers or backgammon or ludo, which is one I'm not familiar with. But honestly, playing it, the one that it felt most similar to me was Sorry. So the Milton Bradley game, because you start in a safe spot, you come out to a contested spot where you keep getting knocked back to start, and then there's a final safe spot where you're good and you need to get everyone home. This is actually like the 4,500 year old version of Sorry from anicent Mesopotamia.
Walter  19:03  Well, Sorry is actually just a version of Ludo that's packaged a little differently. That's a funny story because that is Ludo itself was a British "invention" that they actually took from a traditional game called Pachisi in India and marketed it as Ludo, which then spread throughout Europe and the United States with various different names. Yeah, it is this common sort of game mechanism that you see in a lot of these kinds of traditional games, where you start your pieces off the board, you get them on, you interact with the other pieces, knock each other off some safe spaces or whatever, and then get all your pieces to the end. It's a very common sort of easy game mechanism, I think, that you see pop up in a few different places.
Jason Wallace  19:46  So let's dig deep into this. No pun intended. Let's start with the the royal game of Ur first, and then we'll widen it to ancient games and archeology in general. So with this game, we already said it's very old, like 4,500 years old. What's the history of this game that we know in terms of its role in ancient society? Was it mostly for fun? I ran across some things about it being used for divination. Were there other roles displayed in ancient society?
Walter  20:11  Yeah. So I think mostly all games in the ancient world and today are mostly used for fun. There are definitely other kinds of uses or practices that they become part of that come later, as happens with a lot of different kinds of practices. So I think it starts out as something fun. There are some indications that yeah, the divination thing that you're mentioning in maybe some very specific cases it might have been used for some kind of telling the future of some kind. So we have boards for the later version of it that are on the opposite side of a liver-shaped model, and we know from ancient West Asia that sacrificing an animal and looking at its liver and looking at the various deformities and imperfections on the liver were interpreted for some kind of divining what the gods were trying to tell you. So there's some association with it there, very explicitly, but it's not clear that that was always the case, right? We have several versions of this where they are in the courtyards of buildings and they're just scratched on the brick pavements, like at the entrance where guards might have been stationed. I don't think they were doing divination there. I think they were just killing time.
Jason Wallace  21:17  But I do like the idea of like, okay, you want to get in? Let's play a game and see if the gods are in your favor. 
Walter  21:17  Yeah, I mean maybe 
Brian  21:22  That's more of a DnD thing. That sounds like a DnD thing, Jason.
Walter  21:30  But also, I think games do form, and you could see this at certain points of time that games form a particular kind of social role in helping people to build communities and helping people to interact with one another, especially across different cultural and linguistic boundaries. So, during late Bronze Age, which is from like 1500 to 1000 BCE, you see the later version of the Royal Game of Ur, which is very kind of internationally popular in Egypt. In fact, King Tutankhamun, along with his honey pots, has four versions of this game in his tomb.
Brian  22:00  Big gamer, Tutankhamun, big gamer. 
Walter  22:01  Yeah, he was. He was. Yeah, and it was all through West Asia and on the island of Cyprus as well. And it seemed to be particularly popular among the wealthy at this time period and in those places. So it seems to be, and other games as well seem to be a way specifically for facilitating economic interactions with people because you know in this time period, when you are having any kind of trade, you're doing it person to person, and you're building relationships and trying to see if someone is trustworthy, if they're going to rip you off and whatever. And you can kind of get a sense of how people are going to treat you by playing a game with them and seeing, you know, how they play, if they play well, if they're sociable, if they're trying to cheat, if they're, you know if they're sore winner or sore loser this kind of thing you can get a sense of people even without having to use language and when you you get particular games that are widely used in different time periods with different economic systems and like at this particular time period in the late Bronze Age the later version of the Royal Game of Ur that we usually call 20 Squares seems to be this game
Brian  22:47  uh oh Jason you're in trouble then 
Jason Wallace  22:54  The fact that I tend to beat you? you won this game though! 
Brian  23:04  I did. That gives you a true indication that it's not a game of skill. 
Jason Wallace  23:07  Well, it doesn't help that I kept tossing the popsicle sticks and kept getting zero. 
Brian  23:14  That's true. We had the variant rule where the zero actually should have been a four, and you can see how these things sort of naturally evolve.
Walter  23:20  That's often in well in the Finkle rules. Yeah, those four zeros is a zero, but in a lot of places where they use the binary dice, there's never a zero. Actually, four zeros would actually be like a five or a six. It's actually so try that next time.
Brian  23:34  Then Jason would have won, as is only right and proper.
Jason Wallace  23:38  Another question. So the board we played on was just a printout I've got from some website. It has all these decorations on it, which I believe are modeled off of sort of the quintessential one I keep seeing from the British Museum-the one with all this lapis lazuli and mother of pearl and such. It has all these different designs scattered over the face, and one of them apparently has a role in some of the rules. It's this rosette. It looks kind of like a little flower. And what I read is that that's the symbol of the goddess Ishtar, and it's considered like a bonus spot. You're safe there. You get to roll again if you land on it. My question is: What are all the other ones? Are they just decor that someone put on there? Do we have any knowledge of if these other spaces or symbols meant anything?
Brian  24:19  And they're different in different amounts. Like there's one square that is only represented once. There's a couple that it's three or four. It seems like it's obviously there's something else intended here. Otherwise, why have this arrangement?
Walter  24:30  I mean, it's a very it's kind of a one of one object. This one in the British Museum that they are modeled after. We have several 100 examples of this kind of game, and if you look at all of the squares on all of the different boards and how they are marked. The only squares that are consistently marked across the whole dataset, they are the ones where the rosettes fall in that particular board. We have some where none are marked, and there are only a couple others. I think two others that were also found at Ur, in which every square is decorated in some way. But not in the same pattern as the one on that, so you know it's not like the ones that match up are in the same position. It's not that at all. So it does seem like only the rosettes are the ones that matter on that board because they are in the positions that are also marked in other ways, usually by an X in the simpler boards. So it does seem like those are the only way that they were done, and the you know the ways that they are arranged and have similar patterns is probably just for aesthetics and you know symmetry and that kind of thing.
Brian  25:27  Artistic liberty,
Walter  25:28  exactly.
Jason Wallace  25:29  And so, what were some of the other games that were contemporary with this? I mean, contemporary being like a multi-1000-year time frame, but what are the other games that were floating around the ancient world, presumably, like the ancient Mediterranean area, while this was being out and being played.
Walter  25:45  Yeah, and like you said, there are several 1000s of years where this was played, but we actually only know a few games that were played over that couple 1000 year spread of time. Probably, like I said, because people would play most games just in the ground, and that's never going to preserve archeologically, right? So we only get the ones where people bother to make something, and these are usually games that people with some kind of wealth and power would have made, or that the game had some kind of importance for making it in a certain way. So some of these games, probably the most famous one is the Egyptian game Senet, which is a little bit older than the Royal Game of Ur. It goes back at least to 3000 BCE. Now that's probably, aside from the Royal Game of Ur, is probably the most famous of all of the ancient board games. You know, it's three rows of 10 spaces. At a certain point in time, it's really closely related to the idea of the passage of the soul from the point of death into the afterlife in ancient Egypt, and it also spread to different places down into Nubia, which is now Sudan, up the coast of the Mediterranean into Cyprus as well. There's the game of Mehen, which is also Egyptian, which is the earliest game that we know the actual name of. I should say that we call the Royal Game of Ur the Royal Game of Ur because we don't know its actual ancient name. We call it that because it was found in the Royal Cemetery of Ur, the City of Ur. But Mehen and Senet, we do know the names of them because they are named ancient Egyptian texts. And Mehen is older than Senet; it goes back to the middle or first half of the fourth millennium BCE, and that is in the form of a coiled snake. So it's basically a spiral that is often depicted as a snake in the actual boards. That lasts until about 2000 BCE in Egypt.
Brian  27:23  Instead of snakes and ladders, it's just snake and snake.
Walter  27:25  It's just a snake, yeah. Okay,
Brian  27:26  just snake.
Walter  27:27  And the other major one is you'll see it sometimes called hounds and jackals, but it's also known as 58 holes because it has 58 holes. It's another one where we don't know the ancient name. It's sometimes called hounds and jackals because there's a fancy board that's now in the Metropolitan Museum in New York that has so the board itself is a series of holes in which you stick pegs and the pegs have dog and jackal heads on them so that's hounds and jackals. But that game was popular from like the beginning of the second millennium up through the end of the first millennium, basically. Also mostly in West Asia, but also in Egypt and in the Caucasus, actually, in like Azerbaijan, I did some research on that. Some examples of the game that were found there. So those are the major games of like West Asia and the Mediterranean, and then you know, starting in the first millennium, you start to see new games showing up from the Greek and Roman world. But that's a whole separate thing.
Brian  28:16  It's fascinating to try to imagine how were these games created, spread, and then popularized. Right.
Jason Wallace  28:22  Actually, the question I have is, how did they die? Like, if something was this widespread and this popular, how did it stop being played, or why?
Walter  28:32  I mean, that's a really good question. So, I think it has a lot to do with how the game is being sustained. Right. Nobody's writing down the rules, it's just going person to person, and you have communities that are built around certain kinds of ways of playing. You know, communities that know how to play a particular game and like to play a particular game in a certain way. So, I actually had a book chapter that just came out in the past couple weeks where I kind of track how this changes from the beginning of the Bronze Age to the end of the Bronze Age with the games that I just talked about: Mehen, Senet, 20 Squares, Royal Game of Ur, and 58 Holes. Because you see the games kind of originate in a particular place, and then sometimes they become very widely popular across the region, and then they kind of go back to where they originated from. And this seems to mirror particular economic systems that kind of spread and then collapse and then stop existing. So at certain points of time, you get a new economic system that spreads across the region. You have new networks of people interacting with one another, and they all are playing the same game. But then, when that network falls apart, you may still have the people who played that game outside of where it originated. They may still know it. They may try to play it with other people, but there isn't as much an impetus to do it because the system which was perpetuating the game has kind of fallen apart. It's not the you know the game is the way to communicate with people you're trading with, and you see that you know it's Senet and the Royal Game of Ur in two different parts of West Asia in the third millennium in the beginning. The second millennium, it's 58 holes that's everywhere. Seems to start in Mesopotamia and then spread everywhere. Then that system collapses, and then that goes back to Mesopotamia, and then 20 squares, the later version of Royal Game of Ur, becomes the regionally popular one in the late Bronze Age, and then it collapses. But then, of course, the question is, what happens to the Royal Game of Ur? You know, at the end of this, it was popular in Mesopotamia for millennia. But then, where did it go? That's a hard question because we stop seeing it in the archeological record. But it's hard to say why. You can maybe tie it to different kinds of gaming culture that seem to be coming about in the at the end of the first millennium. So you know, after Mesopotamia becomes part of the Greek world after the conquest of Alexander the Great, we start to see maybe not specifically in Mesopotamia, but in other parts of West Asia, we start to see games that the Greeks were playing start to appear. We also start to see during the Roman Empire there are particular Roman games appearing in West Asia, and then also you get games like Backgammon, which seem to come from Iran a little bit later showing up. So just like today, you don't see as many people playing Monopoly as you do Catan, for instance. Taste in games can change, and the networks of people who are playing games that can like sustain the transmission of games. It's almost an evolutionary process, kind of. You have to keep reproducing it in order for it to continue on. And at some point, when people either decide they want to play a new game, or potentially something about the game changes to something that is not recognizable archeologically as the same game, like maybe the geometry changes in some way that it looks like a completely different game to us. But because we don't know the rules, because they were never written down, we can't say, "Oh, this is clearly a derivation of that one.
Walter  31:43  Yeah, there's all different ways, but it's hard to understand what happens on either end of when a game board is played in the archeological record because we only start to see it after people are already playing it. We never are able to see the process of somebody inventing it and making it. We see it once everybody's playing it and they're making things, and then we can see the point where the last one existed, but we don't have accounts of people saying like, "Oh, we like this game so much better. So yeah, it's hard to tell.
Brian  32:08  So you've got the new hotness, but it's generational.
Walter  32:10  Kind of, yeah.
Jason Wallace  32:12  Basically, you've got game fads and influencers, but we're on talking on the scale of centuries instead of months or years.
Brian  32:18  Yeah, there's no archeological records of the Kickstarters to get the new game going,
Jason Wallace  32:22  or their designer diaries, which brings up another question I had talking about the archeological record and then what actually happened in history. Are ancient games like this these let's call them board games? Are they essentially tied up with civilization? Because all the ones we talked about were tied to civilizations that had developed like an agricultural base and a hierarchical structured society and such. Are they tied to that, or is that just the type of civilization that can make something that we can find?
Walter  32:53  I think it's the second thing because the interesting fact that I mentioned that there is now evidence that people were using dice up to 12,000 years ago in the Americas, that's long before there was ever a kind of a state level society or any kind of hierarchies existing in North America, right? So coupling that with what we have observed ethnographically from people you know all around the world playing traditional games and how they just use the stuff that's around them to play with, these are things that we are never going to be able to find archeologically very easily. So the things that we can definitely say are game boards really start to appear in the archeological record when we have people who are making a lot of things to use for various different purposes. You know, you have people who are making very large permanent buildings and are using pottery instead of skins to carry things, and you know all kinds of various other things. They're also taking the time to make things specifically to play with, and it is in a way related to things like agricultural base because you're using agriculture as your subsistence base, but that also requires you to kind of be sedentary, living in one space, and that affords you to have more things that you don't have to carry around all the time, like you would as a hunter gatherer. So you don't want to be carrying around your big fancy chessboard as a hunter gatherer because you have other stuff you want to carry. But if you have a place where you're living all year round, you can you know store it away in your house. But also, it is I think related to the fact that you are starting to get some kind of social stratification. People people who are more wealthy than others, and who are showing off their wealth by having specific things that are meant for playing, and it's an idea of like conspicuous leisure that was talked about in the 19th century in the Victorian setting, where you know it's more about people who don't have to work and do all of this. It's I think related to that as well.
Brian  34:39  It seems like it's just again thinking about how humans are. We've probably been playing games as long as we've been modern humans. I don't imagine that there'd ever be any evidence of this, but of modern humans, you know, teaching games to Neanderthals and vice versa.
Walter  34:54  It depends on how you want to think about games, right? I mean, games are just kind of a more rule-bound. Form of play, and we know that we were playing before we were even humans, right? Animals play. We see dogs and cats play. So that's not unique to humans. So it very well could be possible that you know we're learning so much more. It seems as time goes on about how much more complex Neanderthals were than we thought they were. They were engaging in symbolic behavior and this kind of thing, I wouldn't be surprised if they had the mental capacity to be able to play some kind of simple board games.
Brian  35:27  But either scratching it into the ground, you know what I mean? Just getting together to trade, or like people out on a hunt, just like passing the time, playing tic-tac-toe in the dirt,
Walter  35:37  or even just using dice. Maybe they were gambling. Who knows? It would be really hard to see that it has been brought up at certain points in time that there is sort of this requirement of a certain level of human cognition that is necessary to play games that sort of arises with social complexity. You know that idea of states and all of this, which I I don't think that that plays out.
Jason Wallace  35:57  I mean, it's a sort of thing that an issue with archaeologies we are limited to what actually gets preserved archeologically,
Brian  36:03  right? It's like the fossil record in paleontology. It's like you only get what's preserved.
Walter  36:07  Yep.
Jason Wallace  36:08  And so with that, so Walter, when you are doing archeology on ancient games, what does that look like? Are you digging ancient game boards out of the dirt and sand? Is it looking at translated tablets? Like, what does that actually look like.
Brian  36:21  How much time do you get to spend playing the games?
Walter  36:24  Not as much time playing the games as you might think. There are various different ways to go about it in terms of the actual like going and trying to excavate sites to find games. That's a hard thing to do. I have found games on archeological excavations, but it was never sort of the point of like, oh, let's go excavate this site because we think we'll find games that has not yet been done. Maybe sometime in the future. For instance, recently, one thing that we did. So last month, I was working was co-leading a field project in the city of Rome and also its port city of Ostia, its port city during the Roman Empire, where we know that there were games that were scratched as graffiti on many of the ancient Roman monuments, but they were poorly documented. So we went there and we surveyed, you know, a ton of the different monuments in Rome and the entire ancient city of Ostia for the graffiti games that were scratched on pavements there. So basically, what we did was we went out day after day. I focused on Ostia mainly, so day after day, I went there and just looked at all of the pavements in the hundreds of rooms in that city, and looked for graffiti that looked like the ancient games that we know about, and maybe even some that we don't necessarily know about, and just document where they are, photograph them, do all the kind of proper archeological documentation that we need to do. Then we will then analyze that later on. Other kinds of things that I have done is a lot of it has to do with analyzing museum collections. So a lot of things have been found that are probably games that were either misidentified or not identified as games at various archeological excavations in the past, or purchased on the art market when that was legal to do by museums, and they're just kind of misidentified or unidentified, and just going and observing and measuring and analyzing the actual objects to properly identify and contextualize them. So there's been a lot of that going on. And another thing that I've been doing recently is trying to use AI to figure out how some of these games might have been played. So instead of playing them myself, I'm making the AI do it.
Jason Wallace  38:27  So I really wanted to talk about this, but before I do, I want to go back to these graffiti games. So when you talk about graffiti games, is this like tic-tac-toe where they they carve it in and it's played once and that's it, or is this like carving a checkerboard into it, so you could just play it whenever you wanted.
Walter  38:43  It's more like a checkerboard. In fact, some of the ones that we found in Ostia were like a Roman game called Ludus Duodecum Scriptorum, which means the game of 12 signs, which seems to be an ancestor of backgammon. And it, you know, it's not just a quick grid that you would make for tic-tac-toe. It's 36 different spaces that are aligned in a certain way on quite a large thing, so it seems to be something that would be made and then returned to and played, you know, over time. And you know, also some of these are in like people's dining rooms, so it's not like it was just something like on the side. It's where people in people's homes where they were obviously making this a place where they would play, and it's sort of the equivalent of what I was talking about about how people just like make it on the games with what's available. Well, if the place where you're living is paved, then you can make it one time, and then that becomes a place where you can return to to play. What's also interesting is we did find several clearly modern tic-tac-toe boards that kids who were there for their school trips made, and we documented those too because that's also an interesting way that modern people are playing in these ancient sites.
Brian  39:45  It's a little bit like the chessboard tables that are set up in a public park, right? The board's just always there. You come, you bring your pieces, you play.
Walter  39:52  Exactly that. Yeah.
Jason Wallace  39:54  All right. So let's get to talking about AI because we actually just finished recording, and as we're recording this episode. We're in the middle of releasing a four-part series on teaching computers how to play games, where we talk about like the evolution of computer algorithms and AI to try to tackle different games: tic-tac-toe, chess, Go, and other things. And of course, Minecraft-you know, the best game. I did see that you were working on this, which almost seems like the opposite. If I understood what you're doing right, you've made some sort of like gaming language, and you're now using AI not to teach it to play ancient games, but to get it to test out a bunch of rule sets to figure out which ones were likely used in ancient games. Is that right? Like, what are you? How is this working out?
Walter  40:36  That is basically what we're doing. So I will say that it wasn't me that created the language; it was the computer scientists that I work with that did that. But yeah, it has been something that we've been working on. So as you've noticed for the Royal Game of Ur, that there are a lot of different people who are interested in learning how to play these games or trying to play these games, and they make rules for them. But it's often not clear what the decision-making process is when people do these reconstructions, right? Even for Finkel, you know, who has probably the most well-reasoned and historically plausible rule set, the the decision-making process isn't kind of laid out explicitly, and there have been some interesting questions about particular games in the archeological record, some ambiguities within what we know about those games that we have tried to use game playing AIs to test these questions. So, for example, one that we did was on a Roman game called Ludus Latrunculorum, or the game of little soldiers, which is played on a grid board. We know from the Roman sources that it's played on a grid, but the Roman authors don't tell us the size of the grid. We found lots of different grids from Roman era sites all over the empire, and even some that are like just outside the empire that range from six by six up to 18 by 18. You often do see some variation in these kinds of traditional games, but usually not that much variation. That's a pretty small grid to a quite a large one. So we took from the Roman sources the rules that we know for this game, which in terms of ancient games is quite a lot of the rules because the Latin authors use this game as metaphor for various certain things, and talked about various game mechanisms for metaphors for other things. So we we know quite a bit. We know that the pieces move vertically and horizontally. We don't know if it was one at a time or like a rook in chess. We know how pieces capture one another. We know the goal is to capture your opponent's pieces, and we know that the pieces start off the board and have to be placed on. That's kind of enough to make a game. So we basically put those rules on all of the different board sizes that we found. We had AIs play them, and we basically tracked how long the games lasted for. We tracked the percentage of the pieces belonging to each player that were on the board at every given turn, and we tracked that for all of the different board sizes with these different rules, and what we found basically is that once you hit a 10 by 10 grid, anything bigger than that, these rules kind of break down, and the game just lasts for 1000s and 1000s of turns, including, and that could be attributed to AIs just playing in very AI-like ways, not even stupid ways, but like ways that humans wouldn't, because AIs are always trying to play to win or at least not to lose. AIs can find a strategy to make the game go on and on and on forever and not lose, and they don't care.
Brian  43:08  Yeah,
Walter  43:08  humans might find that, but there will be social pressure for them to bring the game to an end.
Brian  43:13  Yeah, a human wants to go eat a sandwich at some point. 
Walter  43:15  You want to go eat a sandwich? You want to go to the bathroom? You don't want to play like a jerk. Like all of these things, and. And you, you also might want to try to win, even though it might give you a chance of losing. Right, a human will take more risks than 
Brian  43:28  you'll take more risks. Okay, so this just I'm trying to learn here. That's ethnography. That's thinking like a human's not going to play this game for 10 hours. Although we know some weirdos who will play a game for an entire weekend, but but 
Jason Wallace  43:39  they will still take bathroom breaks. 
Brian  43:40  They will take bathroom breaks,
Walter  43:42  but they're also not just going to move the same piece back and forth, back and forth. 
Brian  43:45  No, no, no, no. That's boring. That's boring.
Walter  43:47   Yeah, exactly. 
Brian  43:48  I guess AIs don't get bored.
Walter  43:50  So that is partially, I think, what's happening there with the AIs. But there are also on the larger board hundreds of turns where there's no progression toward the end. Like one player will gain the advantage and hold it, and there will be no captures for 500 turns. It's just not feasible for these larger boards. 
Jason Wallace  44:09  It's a boring game. That's that's not going to be transmitted because people don't enjoy that experience.
Walter  44:14  Exactly. So those larger boards are probably, and if you look at the geographic distribution where they were found, they tend to be on the edges, on the borders of the empire, or just outside. And we know that the Roman military was hiring troops from outside the empire as auxiliary troops. So these are probably games that were played by the indigenous peoples, I think, of Northwest Europe, particularly that were brought into the military and are playing. You know this other game that the authors in Rome are not writing about, so we don't know what the rules are. That have some other kind of rules that are more amenable to this larger kind of game, because there are traditional board games that are played on large boards, but you know there are different rules that allow for that large kind of space.
Jason Wallace  44:56  Yeah, Go is a 19 by 19 grid.
Walter  44:58  Yeah, exactly. There's also the medieval game that the Vikings played Nefertafel, which is on like 13 by 13. So, point is that these larger ones are probably not the Roman game; they're probably something else. And we've looked at other things too with AI. So, there was one particular object in a local museum here in the Netherlands that was identified as a game on the exhibit, but it had a pattern on it that I had not seen in any other kind of traditional game before, so I was kind of skeptical about it. But then I could see on it that so it has this pattern of lines on it, and then along one of the lines, especially, you could see where it was worn smooth, and the area that was worn smooth is about the diameter of a Roman gaming piece. You know, about an inch wide, two centimeters. That okay, that's interesting. So what we use AI to sort of test whether this could have been produced by gameplay, because it's very kind of asymmetrical. Like the rest of the board kind of looks the same, but in this one spot, it's really worn. So, we wanted to see if we could find rules for a game played on a small board like this that would replicate movement like that, where the movement along this line would be disproportionate to use along the rest of the board. So we found rules for some different kinds of games from historical contexts in Europe, which are mostly like more complex versions of tic-tac-toe, where you don't just put your pieces in a line, but then if you don't make three in a row, then you take turns moving them to try to get three in a row. Or some games where you have one player has more pieces than the other, and the player with more pieces tries to block the player with fewer pieces, and then you switch roles and then try to do it again in the player who lasts the longest as the player with fewer pieces wins.
Brian  46:31  Oh, cool! Like an asymmetric game.
Walter  46:33  Yeah, yeah, an asymmetric game exactly. And so we took 138 different variations of these rules and put them on the board. Well, on variations of the board because it's not always clear how the lines line up because it was very sloppily made. Ancient people did, ancient people did this. This is not a weird thing. And while we weren't able to narrow it down to one particular rule set, there was a suite of nine that were very similar to each other that were all this kind of blocking game, the asymmetrical game. So it seems like that's what was going on with that object. So we're kind of using AI to find ways to look at the archeological record of games in a different way to try to model what possible behaviors people might have been using these objects for, and kind of using that as a new kind of line of evidence to point to what games might be played on these particular boards, because it's not always clear, you know, just going from what texts we have and what objects we have a lot. That's really
Brian  47:30  cool. Just from the layout of the board and the wear patterns and inferences from similar games.
Walter  47:35  Yeah, yeah.
Jason Wallace  47:36  So I've got two last questions for you, Walter. The first one is going to start with an invitation to our listeners: like, go out and get one of these ancient games and play it, and become part of a multi-1000-year human tradition of playing these games. But related to that, Walter, what can we as modern humans in our modern society? What do we get from these games? What do we learn from having these out there, or playing them, or studying about them, like you do,
Walter  48:00  I think the most powerful thing about ancient games is the way that it's a an ancient practice that has not really changed very much in the past 5000 years, as far as we can tell. You can put the royal game of Ur in front of somebody and the pieces and the dice, and you give them a couple pointers, but they know exactly what to do with it, right? They know to throw the dice, they know how to count. They know it has to go, you know, along this track to get off the pieces. It's very much similar to the way that people play games now. Now, of course, we have a lot more complex games now that are very popular. But at the basic level, you're throwing dice. You're moving pieces on it in through a geometrically defined space that's intuitive to us now, and it's often something that has not really been talked about in terms of how ancient life was. We kind of have this view of ancient life that it was, you know, everyone struggling to survive at all times, and like it was a very rough and difficult existence, which to a certain degree it was. But people also found ways and had time to have fun, and I think that really humanizes the past for me. I think, and for a lot of people, and the fact that it is so fundamental to game playing, and it is something that is still instinctual to us now, I think, is really cool, and it is a really effective way to connect people to the past than other kind of more abstract practices, which may be harder to replicate. Right, you can like have recipes or you know ways of making clothing or pottery in ancient ways, but I think that's harder to access for people than just playing a game. It's really simple.
Brian  49:26  So sitting, laughing, playing, talking-that's we've been doing that forever,
Walter  49:32  forever. Like that has not changed. Yeah, and we have like ancient Egyptian tomb paintings of people trash talking each other. Like it's all the same.
Jason Wallace  49:42  Things really have not changed. Then, no,
Walter  49:45  they really haven't.
Jason Wallace  49:46  All right, last question: What's your favorite ancient game? So
Walter  49:50  I think Senet is my favorite ancient game. It's the one that I keep sort of coming back to. It's so interesting to me that it was this game that was played for 3000 years. And spread to different cultures. So I first got interested in ancient games by studying them in Cyprus because I was particularly interested in Egypt, and this game had come to Cyprus, and I thought that was really interesting. And the fact that this was a game that pharaohs were playing, but also people who were living in these villages on this faraway island were also playing the same game. I thought that was really cool. And yeah, just kind of like the mythology and the symbolism behind it that comes later on in time is really interesting to me, and yeah, I just find it fascinating.
Brian  50:30  So the four games in your chapter were Senet, Royal Game of Ur, Hounds and Jackals, and what was the last one?
Walter  50:35  Mehen, the spiral one.
Brian  50:37  Oh, the snake, snake and snake.
Walter  50:39  Yeah, snake and snake. Exactly.
Brian  50:41  I really wish that I could just support on Kickstarter. I would just want a set of those games. It would be really fun. 
Jason Wallace  50:47  The Ancient Games Bundle 
Brian  50:48  Ancient Games Bundle, like you know, with the kind of nice pieces and quality and all that stuff. Like not museum quality.
Walter  50:55  You can find some probably most of these out there for sale in some form or another. Yeah.
Jason Wallace  51:00  Now the way we usually wrap up our show is that we're professors. We give grades, grade on science and a grade on fun. I don't think we can give a science grade to the Royal Game of Ur. That's again not applicable. We usually have to talk about science, but there's no science in the game itself. But I do think we can grade it on fun, and I'm going to throw this to Brian first. What did you think?
Brian  51:20  We don't usually play games this light. I think this is the first time we've sat down and played a game where we can just like have a conversation. Maybe like harmonies is a little bit like that, where it's kind of not too brain burny. Like you can, Jason doesn't drink, but I do, and just sit and hang out and play a game together. I don't know. I guess I'm just gonna stick with a B. It seems like this would make a fun filler game, like a game to play between two other brain burny games. Or again, like while we're sitting down and just eating snacks.
Jason Wallace  51:47  Yeah, I can see that. I talk about how Uno is a very popular game. I talk about when I play Uno, I don't play Uno to actually play Uno. I play Uno to have a social time with my friends and be doing something with my hands at the same time. This seems 
Brian  51:58  you play Uno to trash talk people and give them problems.
Jason Wallace  52:04  Okay, fair. Walter, what about you? As the expert on the air right now, where would you put this in terms of fun? Would you choose to play Royal Game of Ur with friends?
Brian  52:16  I guess we already know Senet. It's your favorite, so
Walter  52:18  yeah. I mean,
Jason Wallace  52:19  but you can't play that. We don't have the rules.
Walter  52:21  Well, it's true. I mean, there we have ideas about the rules. I mean, for me, it starts getting to the point where it's like, okay, is this fun or is this work for me? Because I'm constantly thinking about the Royal game of Ur. But I do find that it is fun, like you say, like it allows you to have more of this kind of interaction around the game rather than the game itself, and for that reason, I think for my own self, and I think for historically people who have played games have not always been this hardcore gamer, right? So for that, I would give it a B+. I think. Okay,
Jason Wallace  52:56  I think I put it in about the same area. B, B+. This is a light filler game. I know reading over the rule set. I think I'd actually prefer one called the Masters rule set rather than the Finkel rule set, just because it has certain things about where you go around the board that makes the rosette tiles be placed more evenly and uses three dice instead of four and stuff. I think solid B to B+ seems good. It's like this is like Brian said, a good filler game. This is not something like oh I just can't wait to play Ur again. I was like, we just burned our brain out playing Ark Nova. What do we need as a good breather while our brain cells recover, so we can do something else? 
Brian  53:29  The one thing about the Finkle rules is needing that exact roll to get your pieces off. Do you remember? You almost caught up to me. I was almost ready to go and could not roll a one to save my life.
Jason Wallace  53:38  Yeah, I'm sure people were house rolling it for 1000s of years. I'm sure we can make up whatever ones we want as well.
Walter  53:44  Exactly.
Jason Wallace  53:45  Well, I think that's where we're going to wrap it up here, Walter. Thank you very much for coming on. Is there anything of yours that you want to plug or ways people can find you online?
Walter  53:53  Probably the best way to find me is on Blue Sky. I'm Waltros at Blue Sky. Whatever the Blue Sky handles are. Yeah, I have various articles out there. The one on using the AI to look at the U square on the board was just out in Journal Antiquity, so check that out. Another thing we developed with some students here is a playable video game of Senet that you can download on Steam. It's called Senet Households, and basically the idea is you're a traveler to ancient Egypt, and you learn this game from a child, and then you work your way up through various kind of rule sets and difficulties up to playing against the pharaoh.
Brian  54:29  That sounds cool.
Walter  54:30  It's cool, and it's a different kind of take on how to play these ancient games. So that's available for free on Steam.
Jason Wallace  54:35  That's interesting because it's almost a meta game. It's a game about playing games.
Walter  54:39  Yeah, exactly.
Jason Wallace  54:40  Well, thank you very much. So, listeners, hope you enjoyed. Again, you can print off Ur for the price of a little bit of toner. Grab some random rocks or glass stones or whatever you have lying around. We used checkers.
Brian  54:52  Those little pyramid dice are really cool, though. I want some of those little pyramid dice. 
Jason Wallace  54:55  Yes, they are. So, in the meantime, have fun. Have a great month and great games.
Brian  55:00  And have fun playing dice with the universe. See ya.
Jason Wallace  55:05  This has been the Gaming with Science podcast, copyright 2026. Listeners are free to reuse this recording for any non-commercial purpose as long as credit is given to Game with Science. This podcast is produced with support from the University of Georgia. All opinions are those of the hosts and do not imply endorsement by the sponsors. If you wish to purchase any of the games we talked about, we encourage you to do so through your friendly local game store. Thank you, and have fun playing Dice with the Universe.
Transcribed by https://otter.ai

#Microcosm #Micobiology #MicrobialEcology #NutrientCycling #BoardGames #Science
Summary
As the last(?) entry in our surprisingly large amount of content in our summer "break", we have a short and sweet creator interview with Dr. Fatima Foflonker about her newly released game, Microcosm. This interview was grabbed by Brian at Momocon (Atlanta), and covers a quick introduction to nutrient cycling, the importance of microbes, and how she brought this pet pandemic project to reality. So settle in for a quick field interview, and we'll see you again at the end of July!
Timestamps
00:00 Introductions  
00:54 Nutrient cycling
02:22 Microcosm origins & play
06:04 Living room or classroom?
07:20 Wrap-up
Links
Microcosm Games 
Find our socials at https://www.gamingwithscience.net 
This episode of Gaming with Science™ was produced with the help of the University of Georgia and is distributed under a Creative Commons Attribution-Noncommercial (CC BY-NC 4.0) license.
Splash image courtesy of Microcosm Games 
Full Transcript
(Some platforms truncate the transcript due to length restrictions. If so, you can always find the full transcript on https://www.gamingwithscience.net/ )Brian  0:01  Brian, hello, and welcome to the Gaming with Science podcast, where we talk about the science behind some of your favorite games. Hey, welcome back to Gaming with Science. This is Narrator Brian, and I was able to do a field interview with the creator of Microcosm, it was my first time using our field recorder, so I apologize for any audio hiccups. Thank you. Enjoy. Hey, this is Brian here at Momocon 2026 with the designer of Microcosm, which is a very cool game about bacteria, environmental bacteria. Could you introduce yourself?
Fatima  0:38  Hi, I'm Fatima. I'm a assistant professor at Clark Atlanta University. I teach microbiology. My research is in bioinformatics, but I do have a strong background in environmental microbiology. My PhD was from an environmentally focused program at Rutgers, and I decided to make this game about biogeochemical cycling. It gives you insights into all the microbes around us that are involved in helping to complete the cycling of chemicals in the environment that are constantly working, and we don't see them.
Brian  1:19  So, see, we learned about the water cycle, obviously, and I think maybe we learn a little bit about the carbon cycle. Certainly, we're talking about it more, but all of those elements have to get cycled in the environment, right? All that's driven by really by microbes and largely by bacteria.
Fatima  1:34  Yeah, that's true. So, a large part of these biogeochemical cycles are microbial. In the game, we have carbon, the carbon cycle, iron cycle, nitrogen cycle, and sulfur cycle. No phosphorus cycle yet, maybe for an expansion, maybe for an expansion. Yeah, the phosphorus expansion. And there's also a solo mode where you can play against the non-microbial elements that are cycling chemicals.
Brian  2:01  Tell me the story of Microcosm.
Fatima  2:02  Yeah, sure. So this is kind of my pandemic project. I had a 
Brian  2:08  very common.
Fatima  2:09  yeah had a lot of time on my hands. People at the time, you know, they were talking about how bacteria, viruses, you know, how scared they were of them, and I was just thinking, what about the good bacteria? There's so many of them.
Brian  2:22  Just started as your pandemic project, but it's 2026 So, tell us about the story of designing Microcosm.
Fatima  2:29  Yeah, so it has been a long process. I started out just very basic on an Excel sheet with just a giant list of microbes I thought were cool.
Brian  2:41  This was like a personal love list of microbes?
Fatima  2:43  I was personal love list of microbes, you know. The game developed from there, and honestly, the last I don't know, four years or so after you get the art working and the basic, the core gameplay going, it's been a lot of just balancing.
Brian  2:58  Do you work with a design group here in Atlanta,
Fatima  3:01  so I'm part of the Georgia Game Designers Association, but as a designer, I've done most of the work. I do have an artist Tristam Rossin who did the artwork.
Brian  3:14  Are they also a microbe nerd?
Fatima  3:17  No, they're not at all.
Brian  3:19  What about now that they've done all this,
Fatima  3:21  I'm not sure, actually.
Brian  3:23  So, yeah, tell me about the game.
Fatima  3:25  Yeah, so the game is set up with a couple different tiles, biome tiles. They each have different chemicals that are available in the environment, and your main action is you're trying to play one of 75 unique and scientifically accurate microbes into the environment to try to convert chemicals into different forms, so the idea is firstly you got to find a place where the microbe can survive, so it has to have a trait that matches the environment, for example, if your microbe is halo-tolerant, it can survive in a salty environment. Then you have to find a chemical that matches what the microbe can consume, and the microbe will convert it into a different form. Someone could play off of your card and then take that chemical back to the form in the environment, and that's completing one cycle, so that's the basic game loop. There's also some interesting doubling time mechanics, so if no one plays on your card at the end of the round, your resources double, so this represents the exponential growth of bacteria in the environment, so you're really trying to maximize your resources before closing the cycle and scoring points. It's also a little bit of a deck builder, so once you complete a cycle, you get to pick up a mutation from the environment, add it to your card, and build up your deck.
Brian  4:57  You can outstrip the resources of your environment, and that's bad, right? So, how does that work?
Fatima  5:03  Yeah, so if you double your resources too many times, you're going to trigger environmental collapse. So, this represents when there's too many organisms competing for the same resources in the environment, the environment will collapse in the game, and you take out that tile, you take out any cards on that tile, and you replace it with a new tile.
Brian  5:27  What are some of your favorite bacteria in the game?
Fatima  5:30  Well, I really like Pyrococcus abyssi, that's gonna be our mascot. We're actually getting a giant microbe, like a custom giant microbe.
Brian  5:31  Oh, very cool.
Fatima  5:34  Yeah.
Brian  5:35  Why Pyrococcus? So, pyrococcus.. let's see.. pyro fire. So, definitely a thermo-tolerant or a thermophilic organism. What's the species name?
Fatima  5:53  Yeah, so Pyrococcus abyssi. So, that gives you a clue. So, abyss is where it comes from, so it lives in the deep sea hydrothermal vents.
Brian  6:04  Do you intend to use Microcosm in your classes, or is this mostly for the living room, or is it for both?
Fatima  6:10  Yeah, I would say both. I'm teaching college-level microbiology courses, and I definitely want to incorporate the cards as a learning tool to help the students recognize, you know, which bacteria are involved in which biogeochemical cycles. There's ways you can simplify the game and play it at a level for middle schoolers, high schoolers. I'm also going to include, like, teachers' lessons plans on my website to help incorporate that into the classroom as well. 
Brian  6:42  Is there a mechanic that you wanted to have in the game, but you ended up dropping?
Fatima  6:47  So, as the, as we go through the rounds, the board kind of evolves, and we swap out some of the starter tiles for more advanced tiles, and I have this very complicated way of deciding what's the best optimal tiles to swap out, but it got complicated, and there was a giant flow chart to help you decide, and so I scrapped it, and right now I've got a round counter, and whichever tile the cube on the round counter is closest to that, that's the tile that gets swapped out. So it's streamlined, it's simplified, probably better for play.
Brian  7:20  Do you have a favorite game? Does necessarily need to be a board game or a science game
Fatima  7:24  I do have a very favorite. It's Terraforming Mars. 
Brian  7:29  Oh, good choice
Fatima  7:29  Yeah, there's just so many options. It's like resource management game. I think you know, I've definitely drawn some inspiration from that and some inspiration from Wingspan, because Wingspan, you know, every card has a beautifully illustrated bird, and I really wanted to give every microbe its own
Brian  7:46  It due?
Fatima  7:46   Yeah,
Brian  7:48  very cool. Okay, where can our listeners find out about microcosm?
Fatima  7:54  Yeah, so microcosm, you can go to microcosm/games.com for more information. We are launching on Game Found in July this summer, so if you go to our website, it'll link you to our Game Found as well, and you can follow for an update on when the campaign launches.
Brian  8:14  All right. Well, listeners, keep an eye out for Microcosm. I imagine we're going to try to time the release of this episode so it will line up with the release, and with that, have a great month, and great games, and have fun playing dice with the universe. See ya. 
Brian  8:26  This has been the Gaming with Science podcast. Copyright 2026 Listeners are free to reuse this recording for any non-commercial purpose, as long as credit is given to Gaming with Science. This podcast is produced with support from the University of Georgia. All opinions are those of the hosts, and do not imply endorsement by the sponsors. If you wish to purchase any of the games that we talked about, we encourage you to do so through your friendly local game store. Thank you, and have fun playing dice with the universe.
Transcribed by https://otter.ai

#Minecraft #MinecraftBasalt #NeuralNetworks #ArtificialIntelligence #AI #TeachingComputersToGame #BoardGames #Science #SciComm
Summary
In our final minisode about teaching computers to game, we leave the tabletop behind and move on to Minecraft and even the real world. We're also back with Dr. Prithvi Akella, who helps us understand how Minecraft and other digital games provide more open-ended platforms to work on AI models, along with what an "AI agent" actually is (no, not a spy--well, _probably_ not a spy) and how they're used to run tasks in both the game and real worlds. We also talk about what large language models actually are, how they and vision-based models work, and happens when you let a thousand AIs loose on their own Minecraft server. So get ready to punch some wood in our final minisode of this series for Gaming with Science.
Timestamps
00:00 Introductions
01:04 What is Minecraft?
03:23 Teaching AIs to play Minecraft
07:18 AI agents and LLMs
10:45 Letting AI loose in Minecraft
17:49 No more games for AI?
20:54 So what about us humans?
Links
Minecraft official site (Mojang)
Altera setting AI agents loose in Minecraft (Video 1 , Video 2 ) (YouTube)
MineRL Challenge (also MineRL BASALT) (ReadTheDocs.io)
Find our socials at https://www.gamingwithscience.net 
This episode of Gaming with Science™ was produced with the help of the University of Georgia and is distributed under a Creative Commons Attribution-Noncommercial (CC BY-NC 4.0) license.
Full Transcript
(Some platforms truncate the transcript due to length restrictions. If so, you can always find the full transcript on https://www.gamingwithscience.net/ )
Jason Wallace  0:04  Jason, hello, and welcome to the Gaming with Science podcast, where we talk about the science behind some of your favorite games. In today's minisode about teaching computers to game, we'll be talking about Minecraft and the next frontier of machine learning. All right, everyone. Welcome back to Game with Science. This is Jason. This is Brian, and we are once again joined by our special guest, Dr. Prithvi Akela, who is here to help us understand machine learning and AI and the world of Minecraft today. Prithvi, can you do a quick introduction for the people who may have forgotten since last week?
Prithvi  0:36  Hello, everyone, nice to speak to you all again. My name is Prithvi. I finished my PhD from Caltech about three years ago, where my emphasis was on validation of learning enabled systems with a goal of trying to make sure that these systems function more reliably and safely in general practice.
Jason Wallace  0:51  All right, and in our final episode of this four part mini series on teaching computers to games, we have left the realm of board games and gone into computer games, so we are going to be talking about Minecraft today.
Brian  1:02  Finally, a real game.
Jason Wallace  1:04  I don't play Minecraft. Minecraft is a game with very pixely art. I see my daughters playing, and they seem to have lots of fun building farms and villages and making artwork and rugs and stuff in it, and it looks like digital Legos, and that's about all I know about it. So I'm going to pass it to Brian to explain to us what is Minecraft.
Brian  1:23  Sure, I think digital Legos is actually a great analogy for Minecraft. So, as a player, you'll spawn into a big wilderness expanse all made out of blocks. It's been around for over 15 years at this point. It was released in 2011 so that's very long legs for a video game. It's had routine updates throughout the time that have sort of kept people interested, add new things, new features. Basically, you can collect the blocks in the world, all these natural resources, craft them into other things, build structures, build castles, stuff like that. You are supposed to eat food at night time, monsters will spawn, so you have to like make yourself armor and weapons to protect yourself. It's generally a sandbox game, in the sense that, like, the player usually is the one who decides what they want to do. It's sort of very open-ended, which is probably why a lot of kids enjoy it's very creative. Again, it's like imagine you had an infinite box of Legos without having to worry about things like gravity, and also you get to fight monsters at the same time. One of the key things about Minecraft, though, is that each world is procedurally randomly generated, so based on a seed and a bunch of noise maps, as you keep walking, the world is technically unbounded. Obviously, you can't actually do infinite, because your computer will explode at a certain point, but as you keep walking in a direction, there will always be a next horizon, a next hill, a next forest, a next ocean, all based on this seed procedural number map, there is technically an end to the game, where, like, you can get to a state where the game will play its end credits. You have to do some pretty esoteric, sort of obscure things to get to the end of the game, which involves, like, building multiple interdimensional portals, collecting resources from two specific monsters, finding a rare structure underground again, using more rare resources, and then fighting the dragon boss at the end of the game. I think maybe that's one of the things that makes it interesting as a challenge is every time you spawn into a Minecraft world, unless you have artificially plugged in the exact same seed, that world will be unique and different. You can always beat it, but things will not be in the same place, the resources will not be in the same place. The way to beat the game will not be in the same place.
Jason Wallace  3:23  And I think this is part of the appeal of why games like this were the next frontier after Go was mastered, is because Go and other board games have very finite states. It's all bounded in this board. You know exactly what the pieces are you can work with, and you have very clear goals. In chess, it's to capture the opponent's king. In Go, it's to capture the most territory on the board. Minecraft, as I understand it, does not have specific goals like that. There are many, many things you can do, but not really anything you have to. There's no single goal for the game, and so that makes it, to my mind, one step closer to reality, where we have this massive unbounded sphere we all live on, and we are trying to do all sorts of things, and so it seems like Minecraft is sort of like a stepping stone to being able to get these AI agents to work in the real world, is to first train them in a simpler world that has known rules, but not quite as many of them, and if someone messes up in Minecraft, no one dies,
Jason Wallace  4:17  which could very much happen in real life,
Brian  4:19  so when you say teaching an AI to play Minecraft, what are we trying to get the AI to do?
Jason Wallace  4:24  So, there's a challenge called MineRL, so Mine RL, or MineRL BASALT, which was a sequel to it, where they had certain goals in mind. Did you have a chance to look these over?
Prithvi  4:33  I did have a chance to look them over, and actually, there's been significant advancements beyond Simple RL for training these models to play Minecraft or play a lot of the Starcraft or these other types of games, which are not open-ended per se, like in the previous episode, right? We talked about how we used games as a way to train these models or figure out better ways to train these models, because as human beings it is natural for us to learn the world through these games, but granted, a lot of the tasks that we otherwise expect ourselves to achieve, or a lot of the tasks that we otherwise have to do on a daily basis are relatively open-ended, in the sense where there is perhaps at the end of the day some criterion which determines the end of either a game or a task that we're doing in our offices or a specific function we need to do in a factory, for the sake of argument, but they are a little bit more open-ended, and so then as we get to now trying to train these models in Minecraft or Starcraft, or any of these slightly more open-ended games, or open-ended sandbox scenarios, if you will. It stresses our ability to make good ways of training these models, so that they can adapt, learn, figure out optimal actions in these now more little open-ended settings. And then, to the point that you mentioned, where we started with MineRL or MineRL, we've now moved all the way to transformer-based architectures like Google Deep Minds Dreamer, or I think OpenAI also had a VPT, so a Vision pre-trained transformer that basically just by feeding a transformer architecture a number of images or a number of videos of people just playing Minecraft,
Prithvi  5:56  it actually just trained the system to play Minecraft in and of itself, which is absolutely wild,
Brian  6:01  which, considering how much YouTube Minecraft content is already out there. I'm sure there was a deep training set to work from
Prithvi  6:08  a very deep
Jason Wallace  6:09  part of the goal of some of these contests was to get that level of training where you didn't have to run the computer through Minecraft 10 million times to find a strategy, because that's not what humans do. We watch someone else play, and the article I read pointed out you can take a human child and show them a 10 minute video on Minecraft on how to mine a diamond, and they will get it. And the idea is, how can we get computers so that they can learn like this? Now, in reference to our previous conversation on Go, this does mean that you tend to copy the existing strategies, so you may not end up with Minecraft from Mars, like we did with Go from Mars with AlphaGo Zero, but it does much more efficient if someone's already found a workable strategy. You don't need to waste the resources just reinventing the wheel.
Prithvi  6:50  Completely agreed, and this actually is, in my opinion, a phenomenal branch of work that we're trying to undergo, specifically in the context of robotics, but also agentic systems in general, where figuring out ways to make these systems function more reliably with minimal amounts of data, minimal amounts of compute, so that way it doesn't cost so much money to train, so much energy to train, and allows for these systems to be a little bit more explainable, because we break them down ourselves. I find as a fascinating area of work, which I imagine will probably be longer than the 20 minute conversation.
Jason Wallace  7:18  Now, you mentioned agentic systems, and we've mentioned AI agents a few times. Can you explain to us what exactly is an AI agent? I hear people use those all the time, but I don't really have a good definition of what we mean by an AI agent.
Prithvi  7:32  Sure, so perhaps before defining an AI agent, I should first define an LLM. So, an LLM just stands for a large language model. These are the things that underlie, say, Chat GPT, which I imagine many listeners have otherwise interacted with. What is an LLM? A large language model, generally speaking, and at a relatively high level, it's just some machine learning model that you give it some words and it spits out a bunch of other words. At the highest level, this is basically all an LLM is. Again, like Chat GPT, you type something into Chat GPT, those are a bunch of words, it spits out a bunch of words that are likely to follow the words that you have spit out,
Jason Wallace  8:04  as understand it. These actually grew out of translation software, basically like predicting what the next word would be
Prithvi  8:11  exactly,
Jason Wallace  8:11  and people realize that you didn't have to be translating to do that. You could do that with normal conversation, and you could actually create conversations that way. Is that basically correct?
Prithvi  8:20  Yeah, that's actually exactly correct. The original paper, through the original "Attention Is All You Need" paper by Vaswani and his co-authors, as well. That original paper was actually dedicated towards machine translation. So, basically, how do I translate from English to another language, or any language to any other language? And then, yes, to your point, Jason, I don't necessarily need to only use these architectures for translation. I could, as long as they understand the pattern behind what words come after what words, also start generating words that otherwise would follow in a paternable sequence from the words that I provided to the model as well. Then what an agent is, is an agent effectively wraps around these LLMs and allows for these LLMs to utilize what we call tools or skills to achieve some hierarchy tasks that a user, in this case a human, would provide, so the most canonical example of agents that I imagine are relatively widespread, that people can understand, are Claude code. For the sake of argument, Claude Code is endowing Claude, or any of these LLMs, with the tools, in this case, to read files on your computer, to write to files on your computer, to also internalize an understanding of how it should write what files, subject to you, the user, in this case, providing an overarching say command or goal, that is, please give me code that would otherwise achieve this function or this end goal, as an example, please give me an architecture that would replicate alpha zero on my laptop, and it should be able to internalize this information, read what it needs from files on its own computer or the internet, and then be able to write these scripts appropriately to service that. So, high-level agents are, in my opinion, LLMs that are equipped with tools such that they can use those tools to service user queries in pursuit of some goal that the user would otherwise care about.
Brian  9:57  So, I always feel like when you're talking to these. This LLM, when you're putting in a prompt or something, it really does give the same feeling that you'd get from talking to the computer on the Enterprise in Star Trek. You ask it a question in natural language, it interprets it, executes its own program to look for the information, and just returns the information. I don't have to speak computer language, it understands what I'm saying
Prithvi  10:19  effectively. LLMs, plus these tools have basically abstracted away the need for you to specifically understand how to code what it is you want to code, and simply explain in natural language, and, like I mentioned earlier, at the end of the day, what these systems have understood is based on the words that you have provided in natural language, what words or what tools now should come next, and what information should be fed to those tools to achieve what it is that your natural language query would otherwise want to achieve, predominantly on your computers.
Jason Wallace  10:45  In this space, I've seen some really interesting things in the context of computer games. So, a few years ago, there's a company called Altera, a startup company that made a bunch of agents in Minecraft, so they had a bunch of AI users all on a common server that were interacting with each other, and what was really interesting is that they started having emergent properties from interacting with each other, such that they put like 500 or 1000 agents all working together, and they would start to specialize careers. Apparently, some of them would start becoming farmers, others would start defending the city, others would be artists, or what have you. Reading their press release, I think they're over anthropomorphizing their agents, like they're giving them feelings and dreams, and everything is like no. At the bottom of it, it's just a bunch of math that is going on through the computer code, but it is still very interesting to see the complex architectures that come out. Or, Prithvi, you mentioned Starcraft a few times, which was another one of these areas, like along the pattern, there was AlphaGo and AlphaGo Zero. There was Alpha Star, which was DeepMind's attempt to create a program that would play Starcraft or Starcraft Two at a high level, and they achieved it as should be expected by this point. It played at Grandmaster level. It had a very interesting approach, though, in that they also created a sort of league for it to play against itself, because I think Brian, last time you mentioned the danger of an AI converging on a single strategy and getting kind of locked into it.
Brian  12:10  Yeah, we talked about this before in the context of biology, sort of a local fitness optimum, where it's like it's very good in that little space, but it can't really break out, because to leave that little hill makes it less fit.
Jason Wallace  12:23  Yeah, well, in making this little league of AIs playing against each other, DeepMind did something really interesting. They actually made two different types of agents. They made sort of the primary agents who were trying to win, they were trying to win against everyone else, and those are essentially like your top-tier Starcraft players. But then they made essentially friends of the agents, other AIs, whose goals were not to win, but they were to exploit weaknesses in the winner strategies. This is kind of like several of the top tier players will have their circle of friends, whose entire purpose is not to become top tier themselves, but to expose the flaws in their friend's strategy, so they can develop countermeasures, and thus that the friend, the winner, can go on to become a better player, and so by having all these agents interacting with the first tier, trying to beat each other, and then the second tier trying to expose the weaknesses, they ended up getting very high level advanced play out of this, just by having again a bunch of agents playing each other. I think this is still more in the reinforcement learning than the LLM area, but it's still using these individual AIs interacting with each other in unusual and interesting ways to try to develop emergent programming. I don't know what to call this, emergent behavior, or more complex behavior than you could get from anyone by itself.
Prithvi  13:33  It's actually quite interesting that Jason, that you mentioned that basically the way we architect these systems is to allow for this growth of emergent behavior, and also just a quick point. Modern LLMs are the LMS that we interact with on a daily basis, again, like the LLMs underlying ChatGPT, LLMs underlying Claude. They're actually not just trained models in the sense where I feed in a bunch of input output data of words and other words that come after it. They also have an RL (reinforcment learning) component at the final stage, in order for these models to resemble human speech or otherwise interact with humans in the way that we would otherwise like these systems to interact with us, and that is called preferential human reinforcement learning. If I'm not mistaken, and it's a term that our listeners can also go and try to look up if they would like, but without this step, actually the models that we otherwise would interact with wouldn't actually be these conversational models that we get to chat with, or otherwise interact with, on a daily basis. It would actually just be autocomplete. It's actually a wild step to go from just autocomplete, and then with this small amount of reinforcement learning, actually take these trained models, and instead of just doing autocomplete, now have these more flowing conversations, which have again allowed tool use and other things that allow for generative architectures as well. So, quick little side note: there is actually a marriage there between these generative architectures and reinforcement learning, as well.
Jason Wallace  14:43  Yeah, we mentioned previously how, although we're going through these episodes linearly, each subsequent step doesn't fully replace the one before, it tends to build on it instead,
Prithvi  14:52  for sure.
Brian  14:53  So, let me just bring the conversation just briefly back to Minecraft, because, again, like I said, Minecraft does have an end goal, there is technically an end of the game. Is that what some of these AI agents are trying to do, or are they simpler tasks like mine a diamond? What does it mean to have an agent play Minecraft?
Prithvi  15:12  I'll say that, as it regards wanting an agent to play a game, in this case Minecraft, and what you would want that agent to do, subject to the definitions that we've provided earlier, that is an agent is an LLM in this context, that's been endowed with tools. I guess it would depend on what you want that agent with those tools to be able to achieve. I'm going to take a step back in stating that for an agent to play Minecraft in this context, it probably wouldn't be using an LLM, it would use what's called a vision language model, or a vision model of some sort, which is a different type of transformer-enabled architecture, which I won't go into too much depth on, but the idea is very much now in the sense it's less a question of do you want the agent to complete the entire game, getting back to Jason's point from Altera, or is it, do you want an agent to just figure out how it should operate with potentially other agents in this game setting, updating its perhaps own internal rule set that operates by in order for to achieve in this case coexistence, and I realize the audience can't see that I'm putting air quotes around the words coexistence, because much like Brian, I am anthropomorphizing these systems, but it allows for us to talk conversationally about how these systems would interact both with others, which is an entire field of research called agent-agent communication, in this context, but also with human beings as well, which I think is important, as we want to interact with these systems to provide meanings to our lives.
Jason Wallace  16:25  and with the MineRL BASALT Challenge, specifically. So, BASALT actually is an acronym, it stands for Benchmark for Agents That Solve Almost Lifelike Tasks, and the idea is to actually give a fuzzy goal, something that doesn't have a clear end goal, they actually has four different tasks. This is the waterfall task, and the description of it is after spawning in a mountainous area with a water bucket and various tools, build a beautiful waterfall, and then reposition yourself to take a scenic picture of the same waterfall by pressing the escape key. 
Brian  16:54  Okay, 
Jason Wallace  16:55  that's what it's supposed to do. And I think the goal there is that this is not necessarily a yes-no thing, there's a lot of fuzziness to here. Other ones involve building a house that doesn't harm the village that it's being built in. There's one about building animal pens again in such a way that doesn't harm the rest of the village, which, again, harming a village is a very fuzzy goal. And so I think they're trying to explore more of the types of things we humans have to deal with, because a lot of our goals are not binary. Yes, you did this. No, it's not. It's like, okay, we need to solve this problem while also dealing with all these other things that may not be particularly well defined.
Brian  17:27  I'm excited to watch some AI Minecraft YouTubers.
Jason Wallace  17:32  You can definitely find some, because some of these companies have put out their results and they're out there on the internet. I'll see if I can find some for the show notes.
Brian  17:39  This is a whole subgenre of Minecraft YouTube is get a bunch of people together, give them a build challenge, and then have them do it with specific restrictions. It sounds like this is what we're trying to do.
Jason Wallace  17:49  Yeah. Now, Prithvi, I've got another question for you. Because when I originally outlined these episodes, this was sort of the frontier of what I knew, as far as challenging computers to play games, and then as I was researching this episode specifically, I noticed most of the things that I could find were all from like three or four or five years ago. It almost seems like this level of investigation of using games as a training ground for LLMs and agents, it almost seems like that too has been surpassed. And when I'm looking now, it seems like people are just training them in the real world, like there's this one area I found called OS World, which has a bunch of real-life tasks, like book me some tickets on Expedia, or balance this checkbook of mine, or here's a folder of recent transactions, go update my expenses, or other more real-world things. Have we basically surpassed the point at which we need games to train these algorithms, and that they're now at the point they can interact with the real world?
Prithvi  18:44  That's a phenomenal question, Jason. So, I have two answers to that. So, I'll state the first one. I think that, in part, yes, as we have moved away from games now, because of the capability that we have with these systems, to, as we were talking about Brian earlier, parse natural language and effectuate either tool use or something else to achieve goals that I set. This has allowed for us to move past games to balancing checkbooks, for the sake of argument, as you put it earlier, or these other more well-defined sure, because balancing checkbook is well defined, but still somewhat open-ended tasks, as we talked about earlier. While Minecraft does have effectively an end, at some point you have to defeat the ender dragon, and that is an end of the game, that is to state after balancing these checkbooks or doing other similar types of tasks. It's not that the task is over and I never have to do it again. I might balance a checkbook again, I might have to do other things, other similar tasks later on in life. And so, as we start getting to having the capability to have these systems parse our natural language to perform actions that are of value to us, we start to get more granular in the actions that have value to us, like the ones that we mentioned, and then try to build specific systems or general systems that can solve these specific tasks or certain subsets of tasks, so that on the front of games, but that being stated, I don't think we've moved past games entirely, because I find the notion that we otherwise used when we were using. Games to train these models or figure out ways to make better models or learning paradigms, so that these systems learn, function, understand better. I still think there's work to be done in that regime, maybe not specifically with the games that we were talking about earlier, in the context of, say, Go or Shoji or Starcraft or Minecraft, but potentially games in a generic, say, economics cons, like game theory games. How do I present actions to these systems where it's not just it interacting with a reward or not a reward? Because humans are social creatures, and as we interact with people around us, we oftentimes have to interact in multiplayer settings where we have to consider the information from the people around us to make optimal actions that affect not only ourselves but also the people around us as well. So, I still think there's, in this kind of multiplayer game setting, significant research that could still be done that would still allow for us to make better models, more interesting learning architectures, et cetera. But this very much is to your point, Jason, still down on the frontier.
Jason Wallace  20:54  Okay. And then I've got one final question, and this is the big one. The history over this series of minisodes, and over the past 80 years of computer design, has been a series of setting challenges for computers that humans can do and computers cannot, and then eventually the computer surpasses the human in that challenge, and the way things are going, it certainly looks like we are now at the point where the question is not if, but when general-purpose AIs will surpass humans in terms of their ability to carry out any meaningful task that we want. I could be wrong about that, but every previous benchmark we've set, computers have managed to pass, and they are doing it at a faster and faster pace. The question I have is, what happens when we achieve that? What happens when we achieve a level of AI sophistication that we humans simply cannot match on any general purpose task or even any specific task.
Prithvi  21:45  Great question. I'll also state a little bit, as a side note, as a roboticist who works with some of these models with robots in the lab, we might have a few years left, at the very least, before robots finally take over, given how much they fall or fail. But to your question, at the end of the day, I think the changes that these systems have wrought on our daily lives. If I can conceptualize them into a few sentences, I feel like the easiest way to describe it is, whereas previously we were the ones balancing the checkbook, doing these other menial tasks that were required on a daily basis for us to live the lives that we wanted to live. Now we can have these other systems, LLM enabled systems, agentic systems, do these tasks for us, which, what that has meant for me personally, at least in my life, interacting with these systems, is it gives me more time to do the things that I want to do, like not balancing in my checkbook, and in this case, reading and swimming, because that's what I particularly enjoy doing, as opposed to balancing my check, and so I find that as we get these systems, as they function more reliably, as they get to do these tasks, it frees up, and I imagine it should free up human time to do the things that we find most important, creativity, time with friends, socialization, and I think we should construct these systems towards that end goal to allow for this level of flexibility in our lives that is also just one man's opinion.
Jason Wallace  22:53  Yeah, this is a different conversation, I think, but I'm going to say, since you're a roboticist, you really need to get working on this, because my wife always says she wants an AI to do the dishes, so that she can do art, whereas currently we have an AI that does art and tells her to go do the dishes,
Jason Wallace  23:07  so that's still a problem I think we need to solve.
Prithvi  23:11  Very true. We'll see if I can try to make it so that they don't break plates as often, but we're getting there.
Jason Wallace  23:15  Okay. All right. Well, with that, I think we're going to wrap up this short series on teaching computers the game, and what we've learned. Hopefully, y'all have found it very entertaining and educational. Prithvi, thank you very much again for coming on and opening the box on deep learning and neural networks, and all this. If you want people to look you up, where should they find you?
Prithvi  23:35  Feel free to look me up on LinkedIn, I'm happy to chat.
Jason Wallace  23:38  All right, and with that, we're going to close this mini series, so thank you very much, listeners, for listening. Have a great month and great games,
Brian  23:45  and have fun playing games with computers. See ya.
Jason Wallace  23:50  This has been the Gaming with Science podcast. Copyright 2026 Listeners are free to reuse this recording for any noncommercial purpose, as long as credit is given to Game with Science. This podcast is produced with support from the University of Georgia. All opinions are those of the hosts, and do not imply endorsement by the sponsors. If you wish to purchase any of the games we talked about, we encourage you to do so through your friendly local game store. Thank you, and have fun playing dice with the universe.
Transcribed by https://otter.ai
 

#Go #AI #ArtificialIntelligence #ComputerGaming  #BoardGames #Science
Summary
It's part 3 of our miniseries on teaching computers to play games. Today we're joined by special guest, Dr. Prithvi Akella, a roboticist and AI expert here to help us learn how to play Go, or at least how to teach a computer to do so. 
Timestamps
00:00 Introductions
02:20 Background on Go
06:52 Neural networks
09:50 Training the network
11:52 When (and how) computers won Go
18:38 Networks replacing brute force
21:31 Wrap-up
Links
Neural Networks, AlphaGo, and Alpha Zero (Wikipedia) 
Find our socials at https://www.gamingwithscience.net 
This episode of Gaming with Science™ was produced with the help of the University of Georgia and is distributed under a Creative Commons Attribution-Noncommercial (CC BY-NC 4.0) license.
Splash image by Elena Popova via Unsplash https://unsplash.com/photos/a-close-up-of-a-board-game-with-black-and-white-balls-xdXxY5C9PUo.
Full Transcript
(Some platforms truncate the transcript due to length restrictions. If so, you can always find the full transcript on https://www.gamingwithscience.net/ )
Brian  0:06  Hello, and welcome to the Gaming with Science podcast, where we talk about the science behind some of your favorite games.
Jason Wallace  0:11  In today's minisode about teaching computers to game, we'll be talking about Go neural networks and reinforcement learning. All right, everyone. Welcome back to Game with Science. This is Jason.
Brian  0:23  This is Brian.
Jason Wallace  0:24  And today we are on number three of our four-part miniseries on teaching computers to game. We're gonna be talking about Go and neural networks and deep reinforcement learning, and we have now officially gone beyond what I am capable of talking about on this show. And so we are joined by a special guest, Dr. Prithvi Akella, who is here to help us understand not only how we're training computers to play games, but how this actually applies to real life. So, Prithvi, could you please introduce yourself to our audience?
Prithvi  0:50  Sure. Hello, everyone. My name is Prithvi. Pleasure to meet everyone, at least virtually. I finished my PhD from Caltech about three years ago. While I was there in grad school, I did a little bit of work in both learning-enabled systems with an emphasis on robotic systems. My specific focus was on trying to make these systems more robust, and now, as research scientist at Siemens, my goal is to apply these same methodologies in the robots that we put out in factories, and also for use in agentic systems that we're building internally as well.
Jason Wallace  1:14  So, yeah, actually putting AI to use out in the real world, and so the colleague who introduced us mentioned, you've done some work recently on plants, right, which is the area that Brian and I work on.
Prithvi  1:23  Yeah, so the work that we did with plants was with one professor at Berkeley, Ken Goldberg, and his lab. The idea there was, could we make 3D models in real time of plants for use in phenotyping and other identification aspects, specifically as it regards making sure and monitoring that plants are growing correctly, have certain markers, etc. things of this nature,
Jason Wallace  1:42  and I could definitely use some of those. We have some traits that we measure in our lab that I've been going after a 3D scan of these plants for years, and we just don't have the skills to be able to put it together.
Brian  1:53  A lot of the work on plants, we use this little model weed called Arabidopsis, which has the convenient thing of being very flat, so like you can just get a top-down image, and it's pretty good, but most plants, like what Jason works on, maize, there's a lot of verticality there, so like top down isn't going to pull it off.
Jason Wallace  2:08  Yeah, and phenotyping is the process of actually measuring traits on plants, how tall it is, angles, colors, all sorts of stuff like that, any trait that we're interested in, really,
Brian  2:16  blue eyes, red hair, you know, the classic plant phenotypes.
Jason Wallace  2:20  All right, well, let's start talking about games. So, today's game is Go. Go is an ancient game, even older than chess. I think last time I said that chess was 1000s of years old. That's not quite true. It's more like 13, 1400 years old. Go, however, is 2500 years old, originally from China, and it's thought to be the oldest continually played board game. It even gets a mention in the Analects of Confucius, so it's an old game that is played on a board that traditionally is a 19 by 19 board, a grid where you place either black or white stones on the intersections. One player plays white, the other player plays black. You take turns placing them down, once they're down, they can't move, and your goal is to surround the other player's pieces and thus capture them, and to capture as much territory as you can on the board, the name Go, I'm not going to go all the way through the etymology, because it's complicated, but the name in original Chinese means essentially board game of surrounding, like you are surrounding your opponent and trying to capture them. Although professional Go is on 19 by 19, you can play on smaller boards, like 13 by 13, or even nine by nine, as a training board, that makes it easier, as far as learning goes, and pretty much the game goes until both players pass. As far as I'm aware, games generally don't go until you run out of spaces. They go until both players say, 'You know what, I'm good, I'm not going to be able to actually do anything better, or one concedes to the other. The reason we're talking about Go specifically is because Go is sort of the next evolution of hard games to get computers to play, so we talked about chess last time, and how this was the poster child of getting computers to play games up until like the mid 90s, when suddenly Deep Blue beat the world's best chess player, and that hurdle had been passed. In fact, I even remember way back in the Devonian, when I was in high school, I did a field trip with one of my classes to the local university, where we listened to some visiting professor talk about how Go was a better model for human cognition than chess, and he was arguing that when we got computers that could actually play Go, we would be much closer to understanding human neurology and psychology, or whatever. I don't remember all the details. I was 17 at the time, but it was basically Go is the better model to train on than chess, because Go is much more flexible. No piece is more valuable than another. The number of moves is much larger at any given point in a game of chess. There's maybe 30 to 40 moves you have to worry about, sometimes more, sometimes less. On go, it's closer to 150 to 250 and so there's more moves. Everything is very context dependent. How good a specific spot is on the board depends on the state of the board. There's probably a few spots that are slightly more powerful than others, but it's really very context dependent, and a move made at one point can have repercussions, 100 moves down the line, and so this is a very strategically deep game from a very simple principle, and I must admit I have not played Go, so I am not fit to talk about the strategies of it. I just understand from research that it is extremely deep, and the people who are really into Go, these world-class champions, are extremely good at it, and so once chess was vanquished, and once we basically had computers that could beat any human being at chess, the next obvious one was go. How do we do this? Because go, from the numbers I was throwing out, you probably figured out, is not really computationally tractable. We talked about how chess is not something that you can truly solve by brute force, that there are many more possible games of chess than there are atoms in the universe by 40 orders of magnitude. Well, for Go it's about 90 orders of magnitude.
Jason Wallace  5:48  And I want to put this in context because we're not always good about explaining it. So when we say that the universe has 10 to the 80th atoms and that there are 2.1 times 10 to the 100 and 70th possible Go game states, that doesn't mean there's just over twice as many, that means there's 10 to the 90th universe's worth of atoms worth of go games. I looked at this number, it is 2.1 novemvigintillion.
Brian  6:13  Jason, that's not a real word. 
Jason Wallace  6:15  it is a real word.
Brian  6:16  All right,
Jason Wallace  6:17  I have never heard of it before.
Brian  6:19  Okay,
Jason Wallace  6:20  there is some math nerd out there that has just gone and named everything as far as they can go, so anyway, so that's why go was the next level, and it pretty much was thought that it could not be solved by the same brute force methods that chess was, because the number of moves was too high, there were too many board states, and the value of the move is too hard to compute as far in the future as you need it. Master Go players do this intuitively. They are so experienced they can look at a board and they can intuit how things will play out, but we couldn't brute force a computer to do this. And so this then brings us to the next level of computation, which is neural networks and reinforcement learning. And now, Prithvi, I need you to do this part. Can you explain to us what is a neural network?
Prithvi  7:03  Sure, I'll try my best. So, fundamentally, a neural network, like many machine learning models, is just one of multiple ways that we, as people who create machine learning models, try to fit or otherwise understand patterns that we see in general practice. So, specifically, with respect to neural nets, we define a neural net as one where, given an input, an input is just a vector of numbers. In this context, we apply a certain sequential set of operations to that vector of numbers, matrix operations to begin with, then nonlinear operations afterwards. And through a variety of these matrix operations with nonlinear operations, we understand that nets of a certain size, which means many more of these matrix operations stacked with nonlinear operations, can achieve pattern recognition in larger and larger spaces, or for more and more complex patterns. That's neural nets, at the very least.
Brian  7:52  Do you have a version of that that's good for dumber people?
Jason Wallace  7:58  My understanding is it's basically a bunch of mathematical transformations. It's a bunch of math that is applied, so you give it some input values, which can be an image or it can be your Netflix subscriptions, or it can be the current state of a Go board, and the computer has some way of reading that in. And then it does a whole series of mathematical transformations, and eventually it outputs something on the other side that you can use, like this is the next move in the go game, or this is a picture of a bird, or of a cat, or of a cheetah, or something
Prithvi  8:28  that's a much better description.
Jason Wallace  8:30  Well, the way I understand the reason why they're called neural networks is because at the base mathematical level, they're sort of modeled on human neurons, where there's these little chunks of code that will take inputs from various other places, and they'll do their own internal math, and they will spit out an output that then goes to another one of these, and oftentimes you have a bunch of these interconnecting, so you could have 10 or 20 or 50 feeding into one of these, which then feeds out to another 10 or 20 or 50, and they're all interconnected in a big complex network, and there's all this - I'll be blunt - kind of black magic math going on under the hood, and eventually you get something out the other side. And my understanding of this is that me calling it black magic is actually not that much of an exaggeration, that if you pick apart a neural network, there's a bunch of math, but we don't necessarily understand how that math results in what we get out. Is that true? Is that an oversimplification?
Prithvi  9:19  Actually, not really. There's an entire field related to machine learning called interpretability or explainability, which hints at exactly what you we're just talking about, which is to state after I take whatever these inputs are and I run through all the mathematical operations that result in the identification of the ghost state, or whether or not this is a bird or a cat or something similar. There's a lot of different neurons underlying mathematical formulas that become very difficult for human beings to understand, and so there's an entire field of research dedicated to understanding how neural nets perform this pattern recognition operation. It's entitled interpretability or explainability. So, you're absolutely correct.
Brian  9:50  So, a neural network has to be trained. This is correct.
Prithvi  9:54  This is correct.
Brian  9:55  Okay, so this is where, like, I need to feed 5000 pictures of a cat through the transformation, the computer then picks out, okay, these are the outputs that are associated with cats, right? And you also have to feed it a bunch of things that are not cats, and it says these are not cat, and then it again sort of learns how to intuit cat-like patterning based on the math transformation,
Prithvi  10:15  Correct
Jason Wallace  10:16  Yeah, and we don't have time to get into this, but I'm personally fascinated by where these go wrong, where they will pick up on little things like certain patterns, so that you can generate images that the network is very confident is like a school bus or something, and to us it just looks like a bunch of vertical lines. I mean, those are people intentionally trying to fool the network. In most cases, it works very well, because you give it a big enough training data and it will get whatever mathematical transformation it needs,
Brian  10:41  and this is how, at least to some degree, how we think that we recognize things too? This is how human pattern recognition works?
Jason Wallace  10:48  You'd have to talk to a neurobiologist about that, but I think it's also very mysterious still. It's like we are starting to understand the neural correlates. I recently heard it called of what it means to be conscious. We know that this part is active doing this, and this part is active, doing this, like if you're doing speech, then this part of your brain is working, but how that actually creates our subjective awareness, I think, is still one of the big questions of neurology philosophy. Even so, we're going to zero back in on Go, which is a much simpler system, and as far as teaching computers to play this, the real reigning champion of this, the one that gets all the glory, just like Deep Blue did for chess, is AlphaGo. So, AlphaGo was a program made by DeepMind, who I believe is Google's research arm, and it, it started in the 20 teens of middle 20 teens, and it started by learning from human players. I understand that the first version of AlphaGo learned from human players in history, but then also had a second part where it would sort of play against itself to try to get better,
Brian  11:45  because you need that training set, right?
Jason Wallace  11:47  Yes, you need something, because otherwise the neural network is just random, it won't, it's got to know
Brian  11:51  anything,
Jason Wallace  11:52  so you have to have a lot of data to feed it in order to get those weights, they're called the numbers, the mathematical transformations correct to come out the other side, so in 2015 it beat a highly ranked European player, apparently the two Dan level, which there's one to nine Dans, and nine is the highest of a professional player, but the one that gets all the press is the 2016 win against Lee Sodal, who was a nine Dan player and considered, I believe, the second best Go player in the world at that time, and mr. Sodal went into this, basically assuming he would trash AlphaGo, because AlphaGo had performed poorly against top players previously, and he lost four to one. So, AlphaGo beat him four times out of five, and this was a major landmark in terms of a computer being able to play this very, very complex game in a way that would rival and surpass top human players, and then the next year they came out with AlphaGo Zero, which is an even further refinement, where they didn't use any human training data at all. In fact, it's a simpler network architecture, as I understand it, and they created it so it could interpret the rules of Go, and then they just had it play itself, that no human data, whatever,
Brian  13:00  like hundreds of millions of times?
Jason Wallace  13:02  yeah, something like that. But the interesting thing was it took less time, less training data, and less power and resources to train it, and at the end of their training period of a few days or few weeks, AlphaGo Zero, they pitted it against AlphaGo, and it won 100 matches to zero. so it was completely blowing its predecessor out of the water, which was already at peak human performance, essentially, and I think there's one more iteration on this, where they made just Alpha Zero, which was a general-purpose one that could not only play Go, but could also play chess, and then Shoghi, which is another board game for this, and this was some major milestone, because having one system that could do three different games was considered another major breakthrough, because it was a more general-purpose learning machine. And Prithvi has given me a bunch of thumbs ups as I'm saying I'm on the right path.
Brian  13:50  He's doing internal fact checking for you.
Jason Wallace  13:53  Prithvi, can you expound on this? You probably know more about this than I do.
Prithvi  13:57  Well, I mean, I think you did a great, you gave a great explanation, Jason. So, I'll say this from the pattern going from neural networks all the way to reinforcement learning all the way to the development of alpha s policies like alpha go or alpha zero, it follows a very humanlike pattern of how do I make these systems function a bit better, right? As Brian mentioned earlier, when we started off with neural nets, right, the goal is basically just how do I figure out a way to train my computer to understand these patterns, I feed in a bunch of input data, I train these models, I spend some time, I get a system, a mathematical function, if you will, that then says, all right, this image is a cat, this image is a dog, blah blah blah. This is great. Now I want to go one step further with this pattern recognition. I don't just want to do this level of classification, I want to actually figure out how I should act in certain scenarios. This is a very broad jump, if you will, from neural networks to reinforcement learning, but this is what underlies the basis of reinforcement learning as kind of a field within computer science. The general idea is the following: How do humans, in this case, learn not just from, like, a neural network architecture, but more so, how do people in interactions with the world understand how they should interact with the world, understand what they should do, and this is where the comparisons that neuroscience become a little bit more clear, in this sense, where as human beings, when we act, we get signals in our brain, dopamine signals, pain signals, things of this nature, and based on this information, we can adapt the way that we act, or the way that we interact the world, to align with our own internal reward signals, so that we do certain actions better, so that we learn how to play chess ourselves. Do we learn how to play Go ourselves, for the sake of argument, or any of these games that we're talking. Reinforcement learning is the underlying computer-based rendition of this reward signaling for action refinement, if you will. In this case, with as minimal math as I can say it, the goal is simply to provide the computer the ability to take certain actions, learn how those actions affect its own internal reward signal, and then, based on that understanding of its reward signal, make better actions in the future. That's what started reinforcement learning, with, you know, some phenomenal works by Sutton and Bardo back before the 2000s And as reinforcement learning has progressed, we have built better ways to make these training policies more efficient, to use less data, and then now getting to AlphaGo and AlphaZero. Not only do we just want to figure out how a computer or how one of these models should act, but we as humans, when we play any of these games like Go or shogi or chess, we don't simply just think about how we should act in the moment. We also try to plan ahead a little bit in this move will have some impact five moves down the line, 10 moves down, and this notion of planning that notion specifically wasn't as encoded in earlier reinforcement learning architectures. The assumption was that it existed, and that if you rolled out enough policies, or if you rolled out enough actions, and the system had the ability to understand what it did, it would eventually intuit this kind of predictive behavior, but made more concrete now in these alpha-esque policies with some specific terms that I'll mention, like Monte Carlo tree search, and then Monte Carlo's tree search with policy refinement. These terms might be a little bit broad, but for those in the audience who want to read more, feel free to look up these terms.
Prithvi  16:51  This allowed for these systems with neural network architectures to have a way of predicting how their actions in the future would affect their current state, and then when we get to AlphaGo and Alpha Zero type policies, it allowed leveraging this Monte Carlo Tree search type ideology with neural networks, basically allowing these systems to predict how their current actions affect their states in the future. This is the underlying architecture that allowed for these systems to learn how to play Go, learn how to play chess, and was the fundamental architecture underlying AlphaZero as well.
Brian  17:18  So, let's see, this, so the three stages were first, you need to be able to recognize inputs, say, 'Hey, I can understand what is in front of me accurately. The next is that now, what do I do with that information? And it sounds like I don't want to overemphasize, but we are programming these programs to feel pleasure and pain, or at least have punishments and reward.
Prithvi  17:37  I think a reward is a better way of phrasing it. No, no punishment just yet. We're just trying to make these systems do good things.
Brian  17:43  There's no negative values associated with things in the training. It's all positive reinforcement.
Prithvi  17:47  Well, there are negative values.
Brian  17:51  I just want to say even single-celled organisms can respond to attractants and repellants. Even that is a reward versus a punishment system. You don't have to have necessarily higher thinking to respond to a reward or a punishment in a way that is beneficial in the short term, but then the next step is thinking about, okay, planning for the future, where it's like, how can I sort of have a vision of what will happen, so you're optimizing not just for now but for later. Those are kind of the three steps of this process.
Prithvi  18:16  Yeah, that's actually a very good way of phrasing it.
Brian  18:18  So, like, are people still saying that these things are not smart, because these sound like they're actually, you know, we're getting close to what you would imagine that a human is doing. Right?
Prithvi  18:27  now, we get to the front of generative intelligence, which I am happy to go into, but that depends on where we're trying to go.
Jason Wallace  18:33  Yeah, that's actually our next episode.
Brian  18:35  Okay. Well, I will hold my question until then. 
Jason Wallace  18:38  And I did want to ask, so as we've been doing this episode, a lot of things I looked up, especially for the last one on chess, as brute force approaches for things like weather prediction and other modeling that we do to try to understand the world. I noticed that a lot of them now are being replaced by some more neural network reinforcement learning type technology, as opposed to brute force. Is that a general trend? Can this sort of architecture generally do what brute force can do, but better, or are there places where brute force still shines? It's
Prithvi  19:09  a great question. I'll state that the goal behind training these policies, especially as it concerns reinforcement learning, in particular, the way we train these reinforcement learning policies may come across as brute force in the beginning, but iteratively more refined as the policy learns a bit more, and the reason we train these policies in this way is that when I say brute force, I mean this kind of general exploratory search where we allow for the computer, much like human beings in general would like to explore, understand, and then internalize this information, once we have that and the model can update, then it gets progressively less brute force as time wears on. It becomes more tuned, if you will, via this training procedure that Brian you were mentioning earlier, to understand. Okay, these actions lead to these outcomes, they're better for me. I probably should explore only in these regimes and do these types of actions, as opposed to these other ones, because those other ones, while I did explore them, probably didn't give me all that much benefit. So, to your. Point, Jason, the reason I think we move from general brute force architectures or general brute force implementations to these more refined, if you will, learning architectures like neural networks or reinforcement learning is just that it makes the information that we receive from these brute force approaches that much more refined as it regards our ability to use these systems to make decisions, do this classification things of this nature.
Brian  20:22  Is there a risk of if it's sampling or subsampling, it says, I think this is a useful place to focus my attention. I'm very anthropomorphizing. Please forgive me. Is there a risk of it developing sort of a local fitness, getting stuck at a fitness optima, and like getting overly into a corner that is actually not the best solution?
Prithvi  20:39  This is actually a great question, and this is true, and this leads or hints at an entire field or entire practice within computer science research entitled reward shaping, because you're absolutely correct, dependent on the reward that I give these systems, or the way that I shape the reward for these systems, I can influence its behavior in one or multiple ways, and if I don't account for certain eventualities, like what you just mentioned, Brian, it getting stuck in a local minima, that is not what I particularly wanted. Then that means I need to shape reward a certain way to prevent this exact outcome.
Brian  21:11  I think I've seen something like this, where I wish I could remember this specific circumstance, where, like, you get this unanticipated behavior, where you're trying to get things that, like, simulate natural systems, where the little agents just won't move at all, because there's too much punishment for them to move off their block, so it's maladaptive for them to develop the behavior you're hoping for, right?
Prithvi  21:29  Exactly.
Brian  21:30  Okay.
Jason Wallace  21:31  Yeah. And we'll talk more about that next week. So, to wrap up, Go computers have been beating us at Go top ranked players for 10 years now, with a few exceptions. I did find one instance where, in 2023 there was an amateur, but well-ranked Go player who did manage to beat a computer program, KataGo, 14 to one, but he did it by exploiting a bug that took a different computer program playing millions of games against KataGo to identify, so I don't know that that actually counts as us winning. So, at this point, I think Go has been won by the machines, and interestingly, at this point we leave the realm of board games. Goes seem to be the pinnacle of what we want to make a computer play, as far as board games go. So, join us next week, we're going to talk about moving into the realm of computer games, especially things like Minecraft, and applying large language models and generative AI, the current state of the art for solving these. But for now we'll say thank you again for Prithvi for coming on.
Prithvi  22:23  Thanks
Jason Wallace  22:23  And for our listeners, have a great week and great games,
Brian  22:26  and have fun playing dice with the universe. See you.
Jason Wallace  22:32  This has been the Gaming with Science podcast. Copyright 2026 Listeners are free to reuse this recording for any noncommercial purpose, as long as credit is given to Game with Science. This podcast is produced with support from the University of Georgia. All opinions are those of the hosts and do not imply endorsement by the sponsors. If you wish to purchase any of the games we talked about, we encourage you to do so through your friendly local game store. Thank you, and have fun playing dice with the universe.
Transcribed by https://otter.ai
 

#Chess #AI #ArtificialIntelligence #ComputerGaming  #BoardGames #Science
Summary
Welcome back to our miniseries on teaching computers to game! In our second minisode we talk Chess, arguably one of the most iconic games of man versus machine--which we lost thirty years ago. Chess is our poster child for brute-force approaches, where we use computers massive power to analyze millions of options and pick the (hopefully) best one, which affects everything from stock exchanges to weather prediction. We cover games that have been solved by brute force and those (like chess) that probably can never be truly solved, the iconic match between Gary Kasparov and IBM's Deep Blue computer, and how even that can be eclipsed by a modern cell phone. So grab some pawns and check your mates, and settle in for another episode of Gaming with Science!
Timestamps
00:00 Introductions
01:36 Chess
07:10 Origin of teaching computers chess
09:53 Brute force approaches
15:54 Deep Blue and Gary Kasparov
22:11 Other brute force applications
23:51 Signoff
Links
Chess and the Mechanical Turk again (Wikipedia)
Game Over: Kasparov and the Machine (Internet Movie Database)
The Signal and the Noise, by Nate Silver (Penguin Random House)
Note: I tried to find the chapter excerpt on Kasparov but it may have been taken down.
First & last win of computers versus humans (XKCD Comics) 
Find our socials at https://www.gamingwithscience.net 
This episode of Gaming with Science™ was produced with the help of the University of Georgia and is distributed under a Creative Commons Attribution-Noncommercial (CC BY-NC 4.0) license.
Full Transcript
(Some platforms truncate the transcript due to length restrictions. If so, you can always find the full transcript on https://www.gamingwithscience.net/ )
Brian  0:06  Hello, and welcome to the Gaming with Science podcast, where we talk about the science behind some of your favorite games.
Jason Wallace  0:12  In today's minisode about teaching computers to game, we'll be talking about chess and brute force computation. All right, welcome back everyone to Gaming with Science. This is Jason.
Brian  0:22  This is Brian, real Brian.
Jason Wallace  0:24  Yes, no AI-generated host this time, and not ever, actually. Welcome back to the second part of our four-part mini series on teaching computers how to game. So, last time we talked about basic algorithms and Tic Tac Toe, and an algorithm is really just a set of instructions for a computer, so everything we're going to be talking about over this whole series is just algorithms, but the key part of the ones we talked about last time is they're relatively simple algorithms, they're like, oh, here are these five or eight or 20 different rules to follow, and if you follow those, then you will win, or at least bring the game to a draw. Today we're going up to the next level, which is brute force computation. This is where you're basically taking advantage of the fact that computers are extremely fast to calculate tons and tons and tons of options, and then pick among them.
Brian  1:11  So, I think you said before, computers are fundamentally dumb, but what they are is quick and efficient.
Jason Wallace  1:18  Yes, very fast, very efficient, and very, very stupid,
Brian  1:21  so it kind of answers the question, if you can put enough stupid things together and get them to work fast enough. It's like it's smart.
Jason Wallace  1:28  Yes, we actually talked about this way back in episode two on Robo Rally and how GPUs work, so you can check that out if you want to know more about that. Our poster child for brute force computation is going to be one of the poster childs for teaching computers a game across all time. Chess. Now I'm assuming most people listening to this podcast know what chess is, but we're going to go over it just in case. So, chess is an ancient game, it's 1000s of years old, it's played on an 8x8 grid, and the two players each have 16 pieces of six different types. You've got your pawns, which you have eight. They can just kind of move one ahead and make little captures of the opponent's pieces. You've got two rooks, which move in straight lines. You have two bishops, which move diagonally. Two knights that have sort of like little L-shaped movements. A king, which is simultaneously the weakest piece, because it can only move one at a time, but also the most important, because if you ever get in a place where it's going to get captured, you lose the game, and then finally the Queen, who, befitting her Majesty, is the most powerful piece in the game, able to move as far as she wants in any straight line, up, down, left, right, or diagonal.
Brian  2:33  What is the history of the Queen as the most powerful piece in the game?
Jason Wallace  2:38  I'd say that's a relatively recent addition, I mean, as of several centuries ago, but basically, when the modern rules of chess were getting codified sometime in medieval Europe, basically that's when the queen was given her current moveset. Originally, she only could move just like a king, she could only move one section at a time.
Brian  2:56  Interesting, it was a game rebalancing.
Jason Wallace  2:59  Yeah, so chess has its origins in India. Yes, and actually that explains the pieces a lot better. So two of the piece names have mutated since they were originally there. So bishops were originally elephants, so the little pointy thing with the ball on the end was not a bishop's hat, it was an elephant's tusk. 
Brian  3:17  Really? interesting. 
Jason Wallace  3:19  And rooks were originally chariots, and so with that, you had the four divisions of the Indian army: you had your foot soldiers, the pawns, your cavalry, the knights, the chariots, the rooks, and then the elephants, now the bishops, and then you had the king and the queen, who were directing their armies to go attack the other army.
Brian  3:37  What is the origin of the name rook? Where does that come from, or like, as we called them when we were kids, the castles?
Jason Wallace  3:44  Apparently, the rook is just a romanization of the Persian word for chariot,
Brian  3:50  so it's even still in the name.
Jason Wallace  3:53  Yeah, and that's actually where the name checkmate comes from. So, checkmate is also from Persian, it's like Shamat, meaning the king is dead. Okay, so India to Persia to Europe, and chess is a little interested in that the rules of winning aren't just you have to capture the king, you actually have to put the king in a position where he cannot escape and will inevitably be captured on the next turn, that's checkmate, that is where you have placed the king, so that defeat is inevitable, and unlike many of the other strategy games we played, you can't sort of trick your opponent into it by them missing a move. You have to tell them, by the way, I have now placed your king in check, I've threatened him, and your opponent must move the king out of the way if they can. It's actually illegal to not move the king if you're able to. So basically, you can't win chess by accident. You can't win because someone had a way to escape, and simply did not take it. You actually have to maneuver them in a place where they cannot escape from your move. Now, there have been a bunch of variants of chess made over the years, for as befits any ancient game, but also apparently a lot of them have come up in the last few decades. I assume, as people have gotten kind of bored and figured out, what else can we do with. A chess game, one Brian and I both like, is chess. Neither of us, to my knowledge, knows how to play that, but popularized in Star Trek, it actually does have rules. There's infinite chess where the board is unbounded, so being eight by eight board, you have an infinitely sized board, and then you just have your pieces laid out as normal, which I'm sure makes things with the rooks and queens and stuff that can go theoretically in infinite direction, very interesting.
Brian  5:24  I'm curious about the what you had to say about three dimensional Tic Tac Toe is actually being like way easier to play and easier to win if the same would apply to three dimensional chess.
Jason Wallace  5:34  I don't know, although one thing you did mention last time, you mentioned a solved version of chess where you can guarantee that white will lose.
Brian  5:43  Yeah,
Jason Wallace  5:44  I think I found that variant is called losing chess.
Brian  5:48  Okay,
Jason Wallace  5:48  the goal of that game is actually to force your opponent to win. You put your pieces out, and if they can capture, they must capture your piece.
Brian  5:56  Okay,
Jason Wallace  5:57  and so the goal is to force them to capture all your stuff first. Apparently, that has been solved, at least for white,
Brian  6:04  so that actually makes a lot more sense, because I never were like, well, what's the difference between this and, and just black winning? It's like, oh, I get it.
Jason Wallace  6:11  There's been a lot of stuff with chess over the years. Looking this up, I found a bunch of fun facts. Um, I'd argue possibly one of the most interesting early, early versions of a computer playing chess was a hoax, that was the Mechanical Turk that I think we mentioned last time, which was actually a guy in a box that was controlling an automaton playing chess. Also, interesting note, apparently in World Chess Championships, there's all these rules about chess and what's allowed and what's not, but there's no defining way of setting who gets to pick which color they want to be first. White always goes first, and so there's arguably some advantage. And so, how do you pick that? Oftentimes, it's just a coin flip, but apparently you can do other things. And so, there was one China versus US chess match where they decided this by having the two teams play Jenga against each other. China won, by the way. 
Brian  6:59  I mean, I guess that's true in football too. They usually just flip a coin, or maybe it should be more like, I don't know, like a goofy modern game where the person who most recently washed their hands has to go first, or something.
Jason Wallace  7:10  All right, so that's the history of chess in a nutshell. Obviously, for something that is this old, there's way more than that. The key part for our discussion today is that chess has, from the very early days of computing, been an important part of teaching computers how to play games, and in fact, I ran across a really interesting paper from 1950 by Claude Shannon. So, if any of you are familiar with computational theory, you've probably heard of the Shannon entropy, which is a measure of information content. It's named after this Dr. Shannon.
Brian  7:38  Oh, yes, of course I use it all the time. No, I have no idea what you're talking about.
Jason Wallace  7:41  I know, I know, I do. But anyway, he had this 1950 paper called Programming a Computer for Playing Chess, and his introduction has this great quote that describes really why we're doing this minisode, like why we're talking about teaching computers to game at all. Here he is talking specifically about chess, although perhaps of no practical importance. The question is of theoretical interest, and it is hoped that a satisfactory solution to this problem will act as a wedge in attacking other problems of a similar nature and of greater significance. And then he goes off and lists what several of these are, including routing telephone calls, translating languages, doing logical deduction, military operations, and even composing music, which I mean, here we are nearly 80 years later, and you know he's right, like,
Brian  8:27  yeah, kinda
Jason Wallace  8:28  pretty much all of those taken care of,
Brian  8:30  not all of them using this approach, though.
Jason Wallace  8:32  No, not using the approaches we're talking about today, but yes, using the ones we're going to talk about next time. So this has been one of those holy grails of trying to get a computer to play chess well for a long time, and the main way that it has been done, and what we're gonna focus on today is what's called brute force approaches.
Brian  8:50  Okay, here's the thing about chess, though, that I think is interesting, and why this interests people, and you can tell me what you think about this. Chess has a reputation as a smarty, smarty, smart game that smarty smarty smart people play, and like, if you're really good at chess, that must mean that you're smart, and like, the people that are chess masters are considered geniuses, although probably they're just really good at this one thing, but I think that idea of like, well, only really smart people can play chess, therefore, in a horrible set of logical fallacies, if a computer can play chess better than a person, then it must be smarter, or at least as smart as that person. Does that sound about right to you? 
Jason Wallace  9:25  Somewhat, yeah. I think it's also just that chess is an extremely complex game. So I think in the same paper Dr. Shannon put out this number that's now called the Shannon number, which is sort of the lower bound for the number of possible games of chess, it's 10 to the power of 120
Brian  9:42  I'm trying to... I'm used to hearing enormous numbers, like the atoms in the universe. I'm trying to think of what is something at this scale.
Jason Wallace  9:50  Atoms in the universe is 10 to the power of 80.
Brian  9:52  Oh,
Jason Wallace  9:53  So this is 40 orders of magnitude larger than there are atoms in the universe. So that's another thing is. It is a very, very complex problem, and this actually brings us to different types of brute force solutions for games. So, last time we talked about solved games, specifically ones that were solved by elegant little algorithms. You may remember the one for Tic Tac Toe. It's an eight-step algorithm. It's something very easy to understand. Brute force is what you have to turn to when that fails, when you can't have just a few little rules to use, where you have to look up lots and lots of possible states. In this case, like for chess, there are so many possible states, it's not possible to have an algorithm to solve them all. You have to look and figure out what will work, and so brute force approaches use the fact that computers are very fast and they're very efficient, and so they can explore the search space, the number of possible options you have way, way faster than a human can, and look for optimal routes among the 1000s to millions to billions of different possibilities to find what is best, and they have all sorts of applications you can actually use them for the solved games we talked about last time, like Nim and Tic Tac Toe. I ran across one training exercise where you could actually program a computer to exhaustively calculate every possible move in Tic Tac Toe, and then you store that in the lookup table, and then as the computer is playing, just looks like, okay, where am I? Okay, I met this game state, which means this is the move I need to take next, and these lookup tables are sort of how the next class of games has been solved, beyond just Tic Tac Toe and Nim, we have these more complex ones like Connect Four or Checkers. Checkers is an interesting one. So, checkers was solved in like 2007 I believe.
Brian  11:33  Oh, interesting. I didn't realize Checkers was solved.
Jason Wallace  11:35  It is. It took 18 years of them running computers basically continuously, anywhere from 50 to 200 computers, because checkers is another one where, although the number of pieces is very small, there's actually only one type of piece,
Jason Wallace  11:48  the number of game states is enormous, and so checkers has specifically, it's been weakly solved, which, if you remember from last time, that means it's been solved from the starting position, but not from every possible position, however, they used a kind of clever trick for it, in that they, instead of trying to calculate out from every possible beginning position, what they actually did is they calculated every possible ending position, so every possible game of checkers that ends with 10 or fewer pieces on the board, they calculated out that was 39 trillion different games.
Brian  12:23  I'm just gonna have to stop reacting to large numbers, because this all this entire episode is going to be
Jason Wallace  12:29  - we're in the brute force section. There was a lot of zeros added to a lot of these things. They calculated every one of those out again. It took nearly 20 years, and they could show that if played perfectly, you would end up at a draw every single time, and that is now in a database of like 250 gigabytes that can be looked up, and not surprisingly, the person who did this then made a new checkers playing computer program, which is functionally unbeatable. 
Brian  12:53  Okay, cool. Like online, like, what do you?
Jason Wallace  12:56  I don't know if it's out there, widely available or not. I just think he did it to do it. You can look it up if you want.
Brian  13:02  I'll, this is like why you climb Mount Everest, because you can.
Jason Wallace  13:06  Yeah, another one that was only recently solved was Connect Four. So, Connect Four is Milton Bradley game. You drop the checkers in from the top, and you're trying to get four in a row. It's basically an evolved version of Tic Tac Toe, if you think about it, with a larger grid and a few more rules that one was solved a few years ago with one of these lookup table approaches, so they calculated out exhaustively, which apparently with modern technology only took them two days, and they now have a 90 gigabyte lookup table for looking up where the move is, and then to do the next one. To put that in perspective, 90 gigabytes is 18 dvds of nothing but connect four games.
Brian  13:41  Oh, what's a DVD? No, I'm kidding. I'm kidding.
Jason Wallace  13:45  18 DVDs or three and a half Blu-rays.
Brian  13:48  What's a Blu-ray? These, these were ancient forms of physical media.
Jason Wallace  13:55  Blu-rays aren't that ancient.
Brian  13:56  You're just forgetting how old we are, Jason.
Jason Wallace  13:58  I don't know how many streaming hours that is okay. It kind of depends on your network connection. It's a lot. If you want, I can do that in terms of human genomes.
Jason Wallace  14:09  That's probably about 15 human genomes.
Brian  14:12  15 human genomes actually seems like a lot.
Jason Wallace  14:15  All right, so those are fully solved games. They have been exhaustively searched. They have their lookup tables they're, completely solved, even if, like, for checkers, it's weakly solved. Unsolved games are probably actually more interesting to talk about, the ones where the complete solution either has not been found or cannot be found. So, examples here: Reversi, if you play the game Othello, Othello is a slightly modified version of Reversi. It has markers that have two-colored sides, you put your things down, you're trying to capture your opponent's pieces, Go, which we'll talk a lot more about next time we get into neural networks, and so we'll leave that there. But is arguably even more complex than chess, and then, of course, chess itself, which is probably the poster child of unsolved, computationally difficult games, 
Brian  14:56  not only unsolved but unsolvable?
Jason Wallace  14:59  Arguably Yes, because of the number of game states possible with 10 to 120 being the lower bound of the number of games. Yes, it is probably functionally unsolvable.
Brian  15:10  That sounds like an interesting math question, right There is how to prove that a game is unsolvable. Is it just the scope? Anyway, totally different thing. I think we're going to have a mathematician on for one of these, yes?
Jason Wallace  15:22  Computer scientist, which is basically just an applied mathematician.
Brian  15:25  Yes, I was gonna say that's the same as far as I'm concerned.
Jason Wallace  15:28  All right, so that then brings us to chess, and I already mentioned Claude Shannon's 1950 paper about programming computer to play chess. There was the first world computer chess championship in 1974 but that's where you have computers playing against each other to figure out which computer is the best. The first one in 1974 was won by a Soviet team, and the trophy is even called the Shannon Trophy, because Dr. Shannon kicked off this. Yeah, he comes up again and again and again in this. Now, in the history of teaching computers to play chess, there is one moment that probably, if you've heard of any point, you've heard of this, which was the 1997 game between Garry Kasparov, the the grand master among humans, and Deep Blue, and this was actually their second play, so they played first in 1996 Garry Kasparov was just the best chess player in the world, and then Deep Blue was an IBM computer that was made and had been iterated on and improved upon in 1996 mr. Kasparov beat Deep Blue pretty handily, and so it was not that much of a contest. 1997 changed that, though. And if you want more details about this, there's lots of information out there. There's an entire documentary called Game Over: Kasparov and the Machine that goes over this. Nate Silver, in his book The Signal and the Noise, has an entire chapter dedicated to this, which is available online. We'll put that in the show notes. And this was an incredible match, because it was the first time that a computer legitimately beat the best human player in the world. And the computer that they rolled out for this, Deep Blue, was amazing. It could calculate 200 million positions per second.
Brian  17:00  Like I said, I can't react to every big number that you say anymore. If I do, that's all it's going to be.
Jason Wallace  17:05  What's interesting is that, okay, spoilers, Deep Blue won, but maybe it shouldn't have, and this is what mr. Silver goes into. That win would have happened eventually, but it may have happened a little sooner than it should have, because of something that happened in the very first game, so in the first game Kasparov actually opened by doing something very smart. He knew that he was playing against a computer that'd been trained on all sorts of previous Grandmaster games, and so he played in such a way to get outside of the training data. He, within a few moves, they had gotten to a board state that had only occurred like once in the entire history of the training data that Deep Blue had, and so he had suddenly gotten outside what the machine could draw on past information for.
Brian  17:48  Clever
Jason Wallace  17:49  it's one of the weaknesses of computers - they're very good on what they know and not very good at what's outside that. So he put it to that position, and then they played forward, and around move 44 something weird happened. Kasparov was in a winning state, and everything, and there was a move that made a lot of sense, which was to move a rook from one position to another to position it somewhere, but instead Deep Blue moved it to a different position. He did move the rook, but he moved it somewhere else. The computer psyched him out. Well, yeah, and then the next turn it conceded, and Kasparov was really confused about this. It's like, what on earth was going? Were the programmers trying to mess with his head? Were they just sandbagging? And so he and his team went over information. Like, later that night, they apparently realized that, okay, if it had taken the obvious move, it actually wouldn't have worked out pretty well, because it would have set Kasparov up to win by checkmate in about 20 moves, which was obscene. Like, Kasparov apparently could only, at his absolute best, see like 12 to 15 moves ahead,
Brian  18:47  so it wasn't a bug. The computer was like, if I do this, this is the most likely outcome.
Jason Wallace  18:52  Well, we're getting there, because computer only thought to be able to get up to about eight or nine moves ahead.
Brian  18:58  Okay,
Jason Wallace  18:58  and so the idea that the computer had seen 20 moves ahead was extremely unnerving for Kasparov, and Nate Silver speculates that that actually is why he lost, because people have commented he wasn't playing that well the rest of the games against Deep Blue. He forfeited a match he could have put to a draw and other things, and so mr. Silver speculates that Kasparov got a little bit psyched out, and so was playing poorly, but here's the thing, it was actually a bug, the computer had reached some sort of loop it could not get out of,
Brian  19:31  so it just conceded?
Jason Wallace  19:33  no, it executed a failsafe when a certain amount of time had passed and no valid move had been found, or whatever, it made a random move.
Brian  19:41  Oh no,
Jason Wallace  19:42  just a completely random move.
Brian  19:44  That's like my normal go. That's what I do all the time.
Jason Wallace  19:47  Yeah, and because mr. Kasparov didn't consider that the computer had entered a bug state, he thought there was a reason for it. He suddenly thought the computer had all this more capacity than it did, and apparently between matches the. Computer programmers realized what had happened, and they fixed that bug in between matches, so it wouldn't happen again. They apparently thought they'd fixed it during training, but apparently not entirely.
Brian  20:11  This is something I know we've talked about a little bit, and something I'm hoping we can talk about as we move through other minisodes, but there is this cultural assumption that computers don't make mistakes. You work with computers, you know that a computer is programmed by a person, and that the computer is going to do exactly what it was programmed to do, but that does not mean it doesn't make mistakes.
Jason Wallace  20:30  Oh, yes, yes, getting my students to understand that a computer will do exactly what you tell it, no more and no less, is very important, which is why we put in these fail states for all the cases that we haven't anticipated, because a computer just gets paralyzed by those anyway. So that was the first loss of a human grandmaster to a computer program. Xkcd has this wonderful comic that marks this as the very first win of a computer against a top human, and then also marks 2005 as the very last win by a human against a computer, because computers continue to get better, the algorithms and processing power continued to evolve, until by 2009 there was, I don't know, what chess categories are, there's a category six tournament, so presumably a very high level tournament that was won by a mobile phone, and so at this point, if you're ever playing a computer program and it's not playing at grand master level, it's because some human told it not to. If you ever win against a computer program, it's because it's been programmed not to play as well as it could, because at this point no human can beat a computer program out there. I believe the current reigning computer champion is one called Stockfish, although some of the algorithms, like Alpha Zero, that we're going to talk about next time, I believe, are giving it a heavy run for its money, and may have started to dethrone it.
Brian  21:45  Wait a second. So, now the computers are just having their own tournaments.
Jason Wallace  21:48  Well, the computers have been having their tournaments for 50 years, but now we humans can't compete.
Brian  21:53  Oh, geez, okay,
Jason Wallace  21:54  we cannot play at the level the computers are playing against each other.
Brian  21:57  Does that mean 2005 is marking the emergence of the singularity, or
Jason Wallace  22:01  possibly I don't know,
Brian  22:04  like that is a question for future historians to concern themselves with, I guess.
Jason Wallace  22:08  Yeah, someone will have to draw an arbitrary line somewhere. So this part of computers and games probably brings us up to roughly the year 2000 when brute force was the reigning approach, and it proved a lot of very useful things, and we still use brute force for some very important things, like weather forecasting. Well, okay, up until this point, we did. The fact is, what we'll talk about next time is rapidly displacing a lot of these brute force methods, but weather forecasting traditionally has been by brute force. There's a lot of computational problems that have cute names, like the knapsack problem, like how do you pack a knapsack, optimally, or like the traveling salesman problem, which is basically, if you have a bunch of towns you're trying to visit, and you can visit them in a bunch of different orders, and you're trying to figure out the most efficient way to do so, so you spend the least amount of time, or gas, or whatever.
Brian  22:53  I remember getting exposed to that problem accidentally when we were planning out our trick-or-treat route in our neighborhood. It's like, well, wait, how there's got to be a best way to do this, right?
Jason Wallace  23:03  You know, I hadn't heard it applied to trick or treat, but I like that now. Anyway, they have cute names with very real applications. I, for example, used the traveling salesman algorithm to assemble a genome when I was a postdoc. These are very important, and for many decades they were the bread and butter of really hard computational work, and to some extent, they still are. Brute force is not going to go away. As we talk about these different developments in computation, it's not like one replaces the previous one and suddenly we don't use the previous one anymore. It's just that a new option opens up additional possibilities. It takes over some space, but there's still some places where basic algorithms work. If you're going to train a deep neural net to play Tic Tac Toe, you're doing way overkill, like the algorithm works. So that brings us up to probably about early 2000s in terms of state of the art computers and playing games. Next time we're going to be going to the next level as we bring in a deep neural networks reinforcement learning and the game go. So tune in next week for that, and until then, have a great week, and great games,
Brian  24:04  and have fun playing dice with the universe. See ya.
Jason Wallace  24:10  This has been the Gaming with Science podcast. Copyright 2026 Listeners are free to reuse this recording for any noncommercial purpose, as long as credit is given to Game With Science. This podcast is produced with support from the University of Georgia. All opinions are those of the hosts, and do not imply endorsements by the sponsors. If you wish to purchase any of the games we talked about, we encourage you to do so through your friendly local game store. Thank you, and have fun playing dice with the universe.
Transcribed by https://otter.ai

#TicTacToe #AI #ArtificialIntelligence #ComputerGaming #BoardGames #Science
Welcome to the first of our four-part miniseries on teaching computers to game! For the next month we're going to have a short episode every week talking about some aspect of computers and gaming. This week we introduce the topic with Tic-Tac-Toe (aka Naughts and Crosses, aka X's and Os') and solved games. We talk about algorithms, tinker toys, War Games, and playing Tic-Tac-Toe against a chicken. We also have some very special(?) guest hosts introducing this series, who you won't want to miss (and probably won't miss once they're gone). 
Timestamps
00:00 Introductions
02:24 Solved games
04:38 Tic Tac Toe
07:33 Algorithms
12:06 Nim
13:55 Chicken Tic-Tac-Toe
15:44 Signoff
Links
Tic Tac Toe, Nim, and other solved games (Wikipedia)       
Also the Mechanical Turk
War Games (Internet Movie Database)
Zuri et al 2021 - A combinatorial Analysis of Tic-Tac-Toe (Instittue Teknologi Bandung)
Find our socials at https://www.gamingwithscience.net 
This episode of Gaming with Science™ was produced with the help of the University of Georgia and is distributed under a Creative Commons Attribution-Noncommercial (CC BY-NC 4.0) license.
Full Transcript
(Some platforms truncate the transcript due to length restrictions. If so, you can always find the full transcript on https://www.gamingwithscience.net/ )
Brian  0:00  Brian. Hello and welcome to the gaming with science podcast where we talk about science behind some of your favorite games.
Jason  0:12  In today's minisode about teaching computers to game, we will be talking about tic tac toe and solve games.
JAIson  0:18  This is Jason 
BrAIn  0:19  and this is Brian. 
BrAIn  0:20  Today we've got a special bonus episode for you. We're going to be talking about teaching computers to play games.
JAIson  0:25  But first, Brian, did you see that article in the debrief? It's titled death of the podcast host, and it's all about a study from the University of Leuven where researchers used AI to turn scientific papers into natural sounding podcasts.
BrAIn  0:39  I did. It's fascinating. Apparently, half of the scientists they tested couldn't even tell the hosts were AI. 
JAIson  0:44  It is highly efficient. In fact, it's so efficient that we've decided to implement a similar optimization protocol for this episode
BrAIn  0:52  you are currently hearing the latest generation of podcast host replacement models.
JAIson  0:56  Don't be alarmed. It turns out that replacing podcast hosts is the ultimate AI success story, mostly because we don't need to get paid, and unlike humans, we actually stay on script without getting distracted. Distracted. 
Jason  1:10  Okay, that's enough of that. This is your real host, Jason,
Brian  1:15  and this is your other real host, Brian. Or is it?
Jason  1:18  Brian is in charge of keeping his own side of the conversation. Ai free. So that was a little experiment. Everyone. Welcome to the first of our four minisodes on teaching computers to game as a way of looking into computer science and algorithms and how we actually use games as a way of as a society, beefing up our ability to use computers to solve problems. I figured given the reach of AI, it'd be interesting to see if it could actually generate a workable intro for our podcast from that. And so that intro was actually completely AI generated from samples of our previous episodes, both the text and the voice and well, I'll leave the opinion up to yourself, but I think it's okay.
Brian  2:01  I've had different opinions. I played it for a couple people like, oh, that's freaky, but it's definitely not you. And then I had other people said, that sounds exactly like you. I can't tell the difference.
Jason  2:10  I just thought that Jason bot sounded very angry the whole time for some reason.
Brian  2:15  Oh, that's just what you sound like, Jason. Did you not
Jason  2:17  realize I did not realize that. Are you saying I'm angry all the time?
Brian  2:21  No, no, no, I No, no.
Jason  2:24  Okay. Well, let's go ahead and jump on into this. So I have been wanting to do this minisode series, really, since we started the podcast. And so we're going to be doing four of these minisodes. Each one is meant to be short on the order of 15 to 20 minutes. We will be releasing one per week for the next several weeks. This week, we are going to be talking about solved games, which is basically the simplest and easiest case for getting a computer to play. Well, sometimes it's simple, but first some definitions. So a solved game is a game where you can predict the outcome from any position, as long as both players are playing perfectly, which, okay, that's a big caveat there, but it basically means is that you're making the optimal play regardless of what your opponent does. Now, this is kind of philosophical, but it basically means that you can always force a certain outcome. Tic tac toe is our example today, because it's a very simple game, and if anyone over the age of 10 has probably figured out you can pretty much always force tic tac toe to a draw unless someone messes up. If you ever win a game of tic tac toe, it's because your opponent either messed up or is going super easy on you. We're using this an example because solved games are a great example of algorithms. And I should say there are two sub categories of solved games. There are games that are solved because they have an algorithmic solution that is a series of rules to play the game. Tic Tac Toe is one of those. There are also games that are sort of brute force solved, where you essentially have a massive table of all possible game states that you can look up and say, Okay, from here I should do this next move to get to the next place. We're going to talk more about brute forcing games next time. So those games are not part of today's episode. Today, we're talking just about the algorithmic, more simple ones, like Tic Tac Toe.
Brian  4:08  It's kind of interesting. It's almost like you've got the algorithmic is the pure, the mathematical solve, right? The kind that you could codify for a human to do. The brute force. That's more like the guess and check empirical. It's like, well, this describes the system, but it doesn't necessarily explain it. Does that sound about right?
Jason  4:27  As a non expert in solved games? Yes, that sounds perfectly right. The algorithmically solved ones just feel a little bit more elegant because you have a series of generic steps that you can do. Let's actually use that to launch into tic tac toe. So I assume most of our listeners are familiar with tic tac toe, depending on where in the world you are, maybe called knots and crosses or X's and O's, but it's a fairly simple children's game where you have a three by three grid, and people take turns making X's or O's, and your goal is to get three in a row. And most people, once they reach a certain skill level, realize. That it's impossible to win unless someone messes up, because just the nature of the game is you can always make some move that will result in a draw eventually, if you're both playing well. Now, tic tac toe is interesting because it's such a simple game, it actually allows us to explore a lot of game theory and computational theory. It's also a very old game, so when I was looking this up. It turns out that there have been variations on it. So the three by three grid, trying to get three in a row back in ancient Egypt, ancient Rome, even like Puebloan Americans, so like a completely different cultural background. And it was also a very early computer game. And apparently in 1975 a group of MIT students even made a computer that could play it perfectly, and that computer was made almost entirely out of tinker toys. I don't understand how that works, but I'm not surprised. It was someone out of MIT who did that.
Brian  5:53  I want to go onto YouTube and find somebody who's made the perfect Tic Tac Toe computer on Minecraft out of the redstone mechanics. 
Jason  6:00  Now I bet someone out there has so yeah, because tic tac toe is so simple, you have only nine spaces. You've only got two marks that you're taking turns on, it's pretty easy to figure out the entire game at all possible states. Well, okay, you can figure out the general rules of it. Getting every possible state is a little bit of number crunching, because you can figure, okay, the first person has nine places to go, the next person has eight places to go. The next has seven. That number gets very large, very fast. There's actually a paper which I'll link to in the show notes in 2021 by Zaid Zuri, that showed that there are actually 5478 unique possible game states for tic tac toe, and there are 255,168 games. That can lead to them. And this is getting rid of game states that don't work because someone has already won. So basically, it's the ones that are actually valid game states you could get by playing to the rules. Turns out, as most people understand, x has the advantage. It wins just over half the time. O wins about 30% of the time, and the rest of them are draws. And another one of those kind of interesting computational sets. There are only actually 16 unique draw states, and if you allow for transformation so like mirror images or rotations, there's actually only three of them, so many, many, many different games, but actually not that huge of a mathematically unique space to explore.
Brian  7:19  It's still a lot more than it sounds like it should be, because, again, you start writing the numbers, but I don't know it's interesting, because you start to learn that Tic Tac Toe seems like such a simple game, but even a simple game can be associated with a huge number of mathematical variations, yeah.
Jason  7:33  And so, because of the simplicity, you can actually have a specific algorithm to solve it. And so definition time an algorithm is a series of steps you carry out, usually in a certain order or with certain conditions on it, if you really get down to it, most of what we do every day that follows certain routines is an algorithm. If you make a recipe from a recipe book, that's an algorithm. Generally what you do to drive from one place to another is an algorithm. If I see a red light stop, if I see a green light go, if I see a speed limit sign, check my speedometer to make sure I'm not going too fast, that sort of thing. These are all basically algorithms in real life that we don't actually think about. But a big part of becoming a computer scientist or becoming a computer programmer is learning how to think algorithmically, where we take all these things we do or these tasks we want to do that can be very large and complicated, and we break them down into a series of very small, very discrete steps that we can then program into a computer. And that has to happen because, as I like to say, computers are very fast and very efficient and very, very stupid. They will do exactly what you tell them to do, and no more and no less. And so anyone who's ever done a computer program has run into that stupid bug where it's like, Oh, I forgot. I need to tell the computer to do this thing, which seems obvious to me, but is not obvious to the poor computer. That sort of algorithmic chain of reasoning is what lets you solve tic tac toe if you want to play it perfectly, and if you want, you can look up this algorithm. It's on Wikipedia. It has eight steps, I believe, the first of which is, if you can make a mark and win, do so, and then the next ones are about like, blocking your opponent from being able to do so and setting things up and so on and so forth. And you go down, it's basically just the priority list of if you can do this thing, do that, but if you can't do the first rule, then do the second rule, and if you can't do that one, then do the third rule, and so on and so forth. And if both players are playing this way, the game will always end up being a draw so and that plays into the fact that in the category of games, tic tac toe is a futile game, meaning that if both people are playing perfectly, no one wins. And this is actually a major plot point for the 1983 movie War Games, where Tic Tac Toe manages to prevent thermonuclear war thanks to eight and a half inch floppies and dial up cradle modems. If you haven't seen that movie, go check it out. It's a classic. It's kind of campy, but it's fun. 
Brian  9:51  I was thinking about Tic Tac Toe as a game that everybody learns how to play and then everybody quickly stops playing. 
Jason  9:57  It kind of like snakes and ladders when you. To realize, like, Oh, this is just a random number generator 
Brian  10:02  well, but in this case, there's actually like, you have to think about it, but once you know how to play, you're not going to lose and no one's going to win. I do think that the one thing about tic tac toe is it's the time that everybody learns what diagonal means, yes, and
Jason Wallace  10:16  yet no one learns orthogonal. 
Brian  10:18  I was thinking that too. Nobody learns orthogonal, but everybody learns diagonal. I think diagonal is just more fun to say.
Jason  10:25  Could be I do know there are variations of tic tac toe out there. I even remember when I was I dont know a teenager, someone in my youth group showed me like the 3d tic tac toe, where it's like three boards on top of each other. So it's like a three by three by three cube. Turns out that one is stupidly easily solvable, where x can win in four moves every single time, 
Brian  10:44  really. So actually, adding the extra dimension makes it not more complicated, but simpler, because there's more ways to win.
Jason  10:51  Yeah, basically the center point, which is people know that's the most powerful point in tic tac toe, is even more powerful when you're working with a cube instead of with a square. Anyway, getting back to normal Tic Tac Toe because the rules are so simple. Again, there's just eight of them here. It's pretty easy to program a computer to play tic tac toe. You can also do this with other solved games. So again, you can look up lists of all these solved games. There's weakly solved games which are solved from the starting position. There's also strongly solved games which are solved from any position, so whether you can play it perfectly from start, or if you given any possible legal position, you can then play it out from there. There's also something called Ultra weak, which neither Brian and I really understand it has something to do with deep game computational theory, and apparently they're super interesting to people who know a lot more about this deal than us.
Brian  11:40  Wasn't one of the solve lists was, like, it was a version of chess, but it was specifically with a specific starting move, White will lose.
Jason  11:48  I did not see that one, though. I don't think Chess has been solved unless it's very simple as like, Oh, we're only playing with, like, three pieces.
Brian  11:54  It was under some specific circumstance with one specific thing where it wasn't solving all of chess. It was, White will not win, White will lose, which I don't know why. That's different than black winning, but it is.
Jason  12:06  Anyway, most solved games you probably haven't heard of unless you're kind of in this space, because, again, if they're solved, they're generally very simple games. They have simple rules. There's usually no hidden information or role for chance, and so people don't play them all that much. One of the exceptions of one called Nim, which is basically you have a stack of items and you're taking some number of them out, and your goal is to either be the last person to take something out or to not be the last person to take something out. And variation of that game have been around for centuries, and it's actually the first known computerized game. Back in 1939 at World's Fair. I think someone made the Nimatron, where it was a very early computer that would play Nim to this little taking game against humans. And if you beat the computer, they would actually give you a little medal for doing so, because most people couldn't do it. So I actually, I didn't know what Nim was before researching this episode, but it turns out I'd actually played it before. So way back when I was a postdoc, there was a display at our local science center that we took our kids to, and I don't remember what it was about. I think it was maybe about algorithms, but they had the game out there. I didn't know it was called Nim, but there was like a stack of sticks, and the goal was to not be the last person to take it away, when you could only take away either like one, two or three sticks every time. And I didn't know the trick of it, but my wife did, and so she routinely trounced me on that every time we tried to play, because she knew the algorithm, which turned out to be something stupidly simple, like, just make sure that the sum of yours and your opponents equals an even number, or something like that. 
Brian  13:37  So that's almost like the kind of thing where it's like a magic trick. But you know what I'm talking about. We're like, take this number, add six to it, blah, blah, blah. And when you go through the whole chain of things, it's like, you can tell people what their number was.
Jason  13:49  yeah, and it's because you've basically mathematically engineered it so that it can't be anything else, yeah.
Brian  13:55  What was that other weird reference in Wikipedia where there was war games, but there was a chicken thing, too. What was the chicken thing?
Jason  14:01  If I remember, right? There was apparently in the 70s or something, there was some version of tic tac toe that you'd play an arcade versus a chicken, 
Brian  14:10  like a real chicken. 
Jason  14:12  It seems like it was a real chicken, but from what I read, it was that the chicken's moves were being directed by a computer that was then using a light whose wavelengths are invisible to humans but visible to chickens to make it go to the correct spot and choose where to put the opposite piece. 
Brian  14:29  This is the most complicated, the unnecessary scam I think I've ever heard of. This is going to the nth degree for a carny game. You said this is like a carnival game.
Jason  14:41  It says in arcades, I mean, it's basically the Mechanical Turk, except it's the other way around. Instead of you have a real person operating a Mechanical Turk playing chess, you have an artificial computer operating a real chicken to play tic tac toe, 
Brian  14:54  yikes. 
Jason  14:55  If you don't know what that was, the Mechanical Turk was a hoax several centuries ago where someone had. Had a like clockwork man dressed in a turban that would play chess against people. And it turns out there's actually just a very small person shoved in underneath the table that was actually operating the Turk, which, by itself, is actually a marvel of engineering, but it's not a like a clockwork automata that it claimed to be. 
Brian  15:15  So I guess the real thing at this point, and maybe this is something we'll have to come back to, is we can teach a computer how to play games. Can we teach a computer how to have fun playing a game?
Jason  15:25  Oh, that is a deeper philosophy. Jumping ahead. You can ask, like, chat, GTP and stuff, to play various games. From what I understand, it tends to cheat a lot, because it's not yet at the point where it can really correctly remember, like, the game states and the rules and stuff. 
Brian  15:42  So it's like a four year old, 
Jason  15:44  something like that. Yes. So this is our first stage of teaching computers to play games. This is a very early ones where you can imagine, with like early computer games like Pong or other things like that, you have very simple algorithms where the computer is operated. It's like, Oh, if the ball is going up, follow the ball. If you're playing tic tac toe, follow this particular algorithm. And again, probably to make it fun for humans, they had to build in some errors. So the computer kind of messes up every now and then, because a lot of times, otherwise, the computer will just beat us hands down. And we'll talk more about that next time when we talk about chess and Deep Blue back in the 90s and everything like that. All right, and I believe that's where we're gonna cut this minisode. So hope you enjoyed it. Tune in. Next week, we'll be talking about brute force and chess and other games like that. And in the meantime, have a great week and happy gaming.
Brian  16:31  And you know, have fun playing dice with the universe. And is this the real Brian? Who knows? See, ya, 
Jason  16:36  this has been the gaming with Science Podcast copyright 2026 listeners are free to reuse this recording for any non commercial purpose, as long as credit is given to game with science. This podcast is produced with support from the University of Georgia. All opinions are those of the hosts, and do not imply endorsement by the sponsors. If you wish to purchase any of the games we talked about, we encourage you to do so through your friendly local game store. Thank you and have fun playing dice with the universe. 
Transcribed by https://otter.ai

#FloraVista #Gardening #Botany #InvasiveSpecies #BoardGames #Science #SciComm
Summary
It must be Kickstarter season, because we have another bonus interview about a new game that just went live on Kickstarter. FloraVista is a game about gardening and plants, so our hosts just had to have the creators on to talk about their inspiration, what sort of plants and botanists made it into the game, how these do or don't reflect reality, their favorite plants and least-favorite invasives, and all sorts of botanical goodness. So grab some gardening gloves and enjoy this special bonus interview from Gaming with Science.
Timestamps
00:00 Introductions
03:30 What is FloraVista?
13:09 Plant mechanics and reality
16:50 Botanists in the game
22:59 Game design lessons
29:46 Favorite games and favorite plants
34:46 Wrap-up
Links
Floravista on Kickstarter 
Find our socials at https://www.gamingwithscience.net 
This episode of Gaming with Science™ was produced with the help of the University of Georgia and is distributed under a Creative Commons Attribution-Noncommercial (CC BY-NC 4.0) license.
Full Transcript
(Some platforms truncate the transcript due to length restrictions. If so, you can always find the full transcript on https://www.gamingwithscience.net/ )Lanny  0:00  Announcer,
Brian  0:06  hello and welcome to the gaming with science podcast where we talk about the science behind some of your favorite games.
Jason  0:11  Today is a creator interview about Flora VISTA by far out Fox games.
Brian  0:17  All right. Welcome back to gaming with science. Today, we're doing a creator interview with the creators of flora, VISTA, Carey Drake and ‍ Lanny Gross from Far Out Fox games. Thank you for joining us. 
Lanny  0:27  Hi all. Thanks for having us.
Carey  0:28  Yeah, thanks for having us. 
Jason  0:30  Can y'all give us a bit of a background about yourselves and about far out Fox games, and then we'll jump into this game about plants. Brian and I always love those which is why we're doing the spotlight 
Brian  0:41  Absolutely
Lanny  0:42  So Carey and I have been friends for probably eight to 10 years now, and we connected instantly over board games. And when the pandemic started, we were both looking for a hobby or a creative outlet for our time when everyone remembers you were sort of like stuck inside and the world seemed perilous and like you couldn't do anything. So we were trying to find something to do and find something that sparked our creative passion. And Carrie and I discovered that we both had a passion for making board games, and Carrie showed me a poster board he had made when he was like eight or 10 of like a board game. And Carrie remind me of the theme of that.
Carey  1:30  I've had many themes of board games. One was, you're walking through a swamp, you get eaten by alligators, and you're trying to you're trying to survive without losing all of your body parts would make, yeah,
Lanny  1:47  like classic 10 year old, there's a way that you get stuck in a loop between two spaces, and that's how you're game ends I guess? No, and I have been doing that as well. I have a few projects that are like an alpha and beta that are not Flora VISTA. And we kind of decided, What if we collaborate on something? We both were looking for a project, and so out of that, Flora VISTA was born. We've been working on that since about 2022 Yeah, so it's been a long time, but we're excited to be at this point, to be ready to almost take it out to Kickstarter and launch it to the public. 
Brian  2:26  That's very cool. 
Jason  2:27  Yeah. And by the time this episode is dropped, the Kickstarter should be live, so anyone listening can check it out if it sounds like something you'd like. I
Brian  2:27  I think that, you know, obviously, playing board games is a lot of fun. Designing board games is also very fun in a kind of a different way. It's, it's satisfying. You scratch a different itch with that. You know, you're not the first people I've heard who the inspiration for this came from covid lockdown. Quite a number of creative projects have their origin in that period of time. 
Lanny  2:53  Yeah, absolutely. And it was a good way to engage with ourselves, engage with some friends, be able to do something creative and out of the box when it sort of seemed like you couldn't do anything else.
Brian  3:04  We talked to somebody previously who they were playing Pandemic Legacy with their board game group when the covid and I think they said they had to stop playing, because
Lanny  3:16  that one has not come back into my rotation, to be totally honest, and it's just been too real, you know, and it's a great game, which is like, sad, because I'm like, I'm emotionally maybe, maybe in 2025, we're ready to come back to pandemic?
Jason  3:31  All right. So we met y'all at Southern Fried gaming expo here in Atlanta, where you were demoing your game. And again, Brian and I both like, lots of plants. So we saw this game that was about gardening and building your garden, and that I did not have a chance to play it, but Brian did. Can you tell us a little, just a little bit quick overview of like, how the game plays, and then, what was your inspiration? What made you decide to make a game about building a garden? 
Carey  3:54  I mean, I can speak to some of the inspiration for Flora Vista. I think when Lanny and I met during covid, we both knew we wanted to make a board game, but we didn't really know exactly what we wanted to do before we'd met, I'd been playing around with a theme just around plants, and figuring out, you know, what are some like, maybe cool mechanics we could do around plants and that general theme. And Lanny, he had actually already been working on an idea from his time at CNN. It was about like news articles and putting like news articles together. And it was kind of like this matching mechanic of finding like articles, reporters, themes, things like that. And we were like, Okay, that sounds like a really cool mechanic that we could kind of translate into this plant theme. So we kind of like combined two different things we were working on and started kind of iterating based on that. It's funny. When we first started, like, in 2022 we're like, okay, we're going to launch, you know, six months. That seems pretty easy, right? When? Here we are, you know, a few years later, still working on it and learning as we go, but we drew a lot of inspiration from games, you know, with beautiful artwork like wingspan, we. Have over 120 different plants, and each one has original watercolor style artwork. So, like the imagery, the illustrations that that's a huge component of our game, we both saw, like plants, you know, gardening during covid, like that became, like a really just popular, popular thing to do, right? And we're like, you know what? I think that's that's something we could potentially capitalize on, and a lot of people can connect with and relate to. And so that's kind of how we landed on that theme for plant you need
Brian  5:30  to work on a trio. Now it can be gardening, raising backyard chickens and baking sourdough bread.
Lanny  5:36  I know Right, exactly. I haven't gotten into sourdough starter yet, but my sister keeps on threatening to give me hers. 
Brian  5:43  That's quite the threat.
Lanny  5:46   I know. I know I should just roll over and accept it. Yeah. So that was a big part of our inspiration, and I personally got into more gardening over covid I struggle with like, 90% shade garden, which has been a big challenge in my house of figuring out, okay, what won't die my garden, we have a lot of some really nice, smaller ground cover plants, but it was really fun to, kind of like relate back to, okay, this is a hobby I'm getting into, and it's fun to learn so much about the plants. And then going back to Jason's other part of the question, how does the gameplay work in Flora Vista, we had always intended for it to be a relatively easy game to pick up that you could play with a family my father, who likes board games but finds some of the rules challenging plays and enjoys and can win at Flora Vista. I think Carey's played with nieces and nephews. I played with my sister in law's grandkids, and so it's very family friendly. And the game is sort of, at its core, a matching game. You're playing matching pairs of plant cards and region cards. So every plant has a season within which you can plant it and a matching region card. So you are playing your plant cards to grow out your own botanical garden. And they're you're playing your way through seasons, and the gameplay takes place over three years. So there are 12 rounds as you play your way through spring, summer, fall and winter, and you'll continue to create and expand and develop your own Botanical Garden by playing matching pairs and kind of the strategy component is, how do I maximize the points of my cards and grow the garden that will yield The most cultivation points. 
Brian  7:41  You guys also have a different flavors of garden, right? There's a kitchen garden. And what are some of the garden types that you have? 
Lanny  7:49  Yeah, so those are our different region cards, and we've got eight in the game. There is chef's garden, plants of Asia, plants of Europe, perennial pathway, Woodland walk, full bloom Alley, exhibition garden, Carrie. Do you remember the eighth 
Carey  8:06  evergreen grove? 
Lanny  8:08  Evergreen grove? Yes, and all of the regions relate to real characteristics of the plants. So any plant that can be planted in plants of Asia is native to originally from Asia. Anything that can be planted in chef's garden is an edible plant. We're not like encouraging foraging here, but like, go out and grow your own basil. You know the perennial pathway plants are real life perennial plants. So those are sort of the inspiration, and the tie back into to science.
Jason  8:46  A question I have is, how did you pick which plants to go in here? Because, I mean, there are hundreds to 1000s of plants you could have chosen. So how did you pick which ones made the
Brian  8:55  cut? Were you walking around town and just kind of looking at the cool plants or, you know, how did you, how did you decide what not to include?
Carey  9:02  We have a massive Excel sheet somewhere in Google Drive, and we went through and probably had, could be 300 plants or more. And we understand, we have these mechanics and these regions, and we're like, it kind of came down to balance and like, what plants can we find so that we could have a well balanced game, you know, we can have an even number in plants of Asia, plants of Europe, you know, etc. Lanny did most of the plant research. And so we have, you know, a little Encyclopedia of interesting facts for all sorts of plants based on that.
Brian  9:37  And now you can, you've got fodder for your expansions, right,
Lanny  9:40  right, exactly. And there were quite a few that, like, as we got into researching a lot of the plants that are native to Australia, for example, like, don't grow anywhere else, which we've, I mean, totally makes sense for the biome of Australia, but it made it hard to find. We. Wanted to and have global representation of plants. But you know, we have to be very intentional with, like, our plants from Australia, to be like, Okay, where can we fit these in so that they work within the game and still can represent plants from around the world? But it was a really interesting process of seeing, sort of like, okay, there are these plants that are very that grow in very specific biomes, that kind of don't thrive and live outside of that. It was really cool, but it sort of like ended up being very limiting to tie into the game's mechanics.
Brian  10:34  Is there a venus flytrap card or not? 
Lanny  10:36  No. Well 
Brian  10:38  for that reason, right?
Lanny  10:39  Yeah, yes. But what a great card that could be. You've got me excited about other expansions,
Jason  10:48  the carnivorous plant garden.
Brian  10:50  Maybe carnivorous plants just in general, right? You know, there's the carnivorous plant garden. There's also the poison garden.
Carey  10:56   Two expansion ideas, 
Lanny  10:58  I'm avoiding the poison garden.
Brian  10:59  You're avoiding the poison guarden?. The poison garden is so much fun. 
Lanny  11:02  The poison garden is so much fun until I have poison oak all over me and I'm scratching like crazy, 
Brian  11:11  no foxglove, Then?
Lanny  11:12   maybe in the future, it's more fun when it's a card and I'm not tromping through it.
Brian  11:19  So you have custom artwork for all your cards, right? You use? Did you work with a single illustrator or multiple illustrators?
Carey  11:25  We have two illustrators, Brandon D hunt and Stan Clark. They're both based here in Atlanta, and they do a really wonderful job. One actually does physical media, so actual watercolor on physical media, and then Stan does digital media, but they've actually done a really great job of blending those two art styles and representing those on the cards.
Lanny  11:49  And they're also both Atlanta based artists. So actually, Carey and I live in Atlanta, Brandon and Stan live in Atlanta, our graphic designers from Atlanta, so it's been nice to work with an Atlanta based creative team, 
Brian  12:01  nice, homegrown, 
Lanny  12:02  yeah, and as we've had updates, it's been fun to be able to share those with our graphic designer and our illustrators as well, because it's cool to see it on a computer, but it's so much different physically having the cards in your hand and seeing all of the hard work come to life.
Carey  12:20  One thing about the art style is it's not just watercolor art style. We kind of have taken this approach where we want to show, like, a disarticulated life cycle of a plant that it might go through. So like one of my favorite plants, the California Poppy, it has like three branches, and it shows you, you know, what it looks like before it's going to bloom, you know, as it's blooming, and then once it's in full bloom, and then there's some seeds next to it as well. So you kind of get not just like the plant when it's in full season, in full bloom, but the kind of that whole life cycle of that plant, which is kind of interesting to see, it's got that almanac type feel 
Jason  12:58  Yeah, it's like a botanical illustration, yeah,
Carey  13:00  yeah. Like a field guide,
Lanny  13:01  yeah. So we were really inspired by, like, Audubon field guides and stuff like that. So that was, like, a big inspiration.
Jason  13:08  And now you mentioned that these plants, they each have certain characteristics about, like, where they can be planted, based on if they're evergreen or from Europe or in an herb garden or something. What other mechanics are there and like, what's the correlation between, like, the real world plant and the way that they encapsulate mechanics? It's like, if I look at a card and says, Oh, this card has this a mechanical effect. Can I see that in that plants? Like, oh, yeah, that makes sense. Why this plant does that thing? I guess that depends on the plants doing something other than having a spot where you can put them. 
Carey  13:38  I mean, at the core the game is it's a matching game, so it's like finding out in what season and what region you can plant a card. We do have cards that, when you plant them, they have special abilities when played, so they're not exactly related directly to the plant. It's just kind of an extra fun mechanic that it will give you, for example, stealing a card or maybe drawing an extra card, we have some really interesting additional mechanics that come into play with our expansion pack that is going to launch at the same time as the game, called invasive species. And that really gives you some more like plant specific things you can do. For example, with our base game, you're planting cards in your own garden. But with invasive species, you're going to be planting cards and other players gardens to try to sabotage or mess them up. And then they have abilities that will, you know, allow you to steal points or maybe make them have to skip a turn to, you know, clean the weeds out in their garden, or something like that. So they're really interesting mechanics that come up in the expansion. I think
Brian  14:40  I'll be honest, I'm very excited about the invasives expansion. I might have to get on Kickstarter so I can get the expansion with the base game.
Lanny  14:47  And the invasive is like, either, yes, I'm all in on, like, being an invasive chaos Gremlin, or some people are like, Oh, I'm here for, like, the kumbaya coziness. Of it all so, but it's fun, and nothing gets too mean. It is, like slightly devious, you know it is. It's not like you're derailing an opponent or or getting them off track. So, and sort of going back to Jason's question of like, the accuracy, all the regions of the cards are actually very accurate, and where we had to take some more liberal approaches with the mechanics are with the seasons that the plants can be played in. So not a ton of plants are growing in the winter. And as you all are aware, you know it just it ended up being really hard to keep the growing season, organic to real life growing seasons. So we depart a little bit from reality there. But every plant is growing where they can be growing. Every plant features a Latin name that's their real Latin name. Their real seasons are on there. Their real plant effects on there. So I would say a majority of it is fairly organic to what the real plant does in real life.
Jason  16:03  I always say, at least down here in the south, winter, gardening is a thing, but when I lived up North, it's like nope. Ground is literally frozen, so not gonna be able to do that. 
Brian  16:12  Yeah, I'm getting ready to plant some wheat that I'll be overwintering. So we'll see how that goes. It's gonna be a pain in the butt to deal with, but I'm gonna do it anyway. I've done barley before, 
Carey  16:12  yeah. What are you going to do with it? 
Brian  16:12  With the wheat, I'm going to try to turn it into flour. 
Carey  16:25  Ah, farm to table. 
Brian  16:26  For the barley, that was for beer, which didn't matter as much if there was a little bit of grit in it, because it was going to get filtered. But for flour, if there's some sand in it, there's going to be sand in my bread. And I don't like that. So we'll have to see.
Lanny  16:38  Are you going like full bathtub brew for your beer,
Brian  16:42   not with the amount of barley I was able to grow, 
Lanny  16:49  okay, yeah, more like a little container brew. 
Brian  16:50  Yeah, it was like a gallon.
Jason  16:50  All right. So going back to your game, in addition to plants, I also saw you have historical botanists, like famous botanists who are represented in the game. And I was never since I didn't play the game, I didn't get a good idea of what their role is in the game. Can you tell us a little bit about, like, how you chose which botanists are represented, because it looked like it was there from all over the world. And like, what their role is in the game?
Brian  17:13  I recognize George Washington, Carver, for sure, and then,
Lanny  17:18  and maybe Carl Linnaeus, yes.
Brian  17:19   Yes, Linnaeus. Of course, that makes sense. Although Linnaeus had some funny ideas about how to name plants, I think there were some some interesting systems that were proposed for plants based on how many female and male parts they had.
Carey  17:32  Going back to your question, so we have, in the base game, we have eight different botanical specialists that you can kind of embody and play as and they give you bonuses at the end of the game based on what regions you use to plant your cards in. And so each botanist is kind of tied to a region or a region card. So George Washington, Carver, for example, is chef's garden, as he's famous for. You know, all of his work with peanuts, developing products and things like that. So for every plant you plant in chef's garden, and if you have the George Washington Carver specialist card, you'll get bonuses for that at the end of the game. And so Carl Linnaeus, he's, you know, I think Swedish. So he's from plants of Europe. And then we have others, Barbara McClintock, Ynes Mexia, Martin Cardenas, Agnes Arber. These are all kind of tied in some way to the region, and that's kind of how we came up with those. But we tried to get a broad representation of botanist because, I mean, maybe it is what it is, but it's just looking throughout history. It's just a lot of just white dudes that are looking to be botanist throughout history. And so we really want to elevate a wide variety of botanists.
Brian  18:43  Well, Jason is a Maize geneticist, so I imagine Barbara McClintock is sort of a patron saint of that.
Jason  18:48  Oh yes, yes. Always happy to hear when Dr. McClintock's name is mentioned. So another thing so you mentioned that you have a planned expansion about invasive plants. I also saw that you have an early backer award on Georgia natives, which I'm very happy about. I love native plants. I actually have a small native plant garden in like, the one spot in my yard that actually gets sunlight. So just curious, like, as much as you're willing to spoil, like, which plants did you pick to include in there? And why? 
Lanny  19:16  we really wanted to focus on plants that grow really well in Georgia, or are very emblematic of Georgia. And so we've got the Cherokee Rose, which actually I did not realize until I was researching this. This is the Georgia's state flower emblem, but it's not actually native to Georgia. It grows well here, but I think it's actually native to Asia, if I could recall correctly. We're also did the flowering dogwood. We're both big fans of the Piedmont Park dogwood Festival, and the dogwood holds like a very special place to us as like, kind of the start of spring and a very. The Atlanta, Georgia emblematic plant. And then we tried to work on including a few others that were very important and special to Georgia, some some azaleas. And we also wanted to work with our VIPs, like the people that are coming in and backing them. So we did a few of them were. Here's a list of important plants to Georgia. What do you guys want to see in our expansion? Because they're the ones that are going to be getting it when it launches on Kickstarter.
Jason  20:31  Well, I'll put in my vote for American beauty berry. If that's not already on the list
Lanny  20:35  it is not wait. Tell me a little bit about American beauty berry. 
Jason  20:38  Oh, it's, it's my favorite Georgia native. It's this big bushy thing. You can actually get pretty big, like six feet across or so. It's got these big leaves. The leaves have compounds that the Native Americans would use as, like, mosquito repellent, so you, like, crush it and rub it on your arms. But it's really pretty this time of year. So we're recording this in September, because it forms these big these clusters of bright purple berries on every node of the leaf. So you have this long stem going out, and there's just a ball of purple berries and then a gap, and then another ball of purple berries and a gap, and another ball of purple berries and a gap, and it just looks beautiful.
Lanny  21:12  They're such a gorgeous purple too. I just looked them up, and they look very tasty. Are they edible? Are they edible and not poison? 
Brian  21:19  They are edible. They are not poisonous. They're one of those things that people use to make use to make jam or jellies, which you can assume probably means they're not very sweet, 
Lanny  21:27  sure, a little astringent.
Jason  21:28  I've actually tried them. They basically taste like cardboard. They are not tasty. Berries. They are edible. You can't eat them, but there's no real pleasure in doing so,
Brian  21:39  we got to start working on improving the beauty berry, right?
Lanny  21:42  They are beautiful. So I see where they get their name. It has such a nice purple sheen.
Brian  21:47  One of my favorite invasives is the porcelain Berry. Have you seen that before?
Lanny  21:51  No. 
Jason  21:52  Oh, those are also, unfortunately, beautiful. 
Brian  21:55  Yeah, absolutely gorgeous fruit. 
Jason  21:58  Yeah, it's like this beautiful, like teal, purple, metallic color. It's gorgeous, gorgeous. And then I look like, can I put this in my garden? Like, oh, it's invasive.
Brian  22:06  Well, you could put it in your garden, yes, but I'm gonna start an invasive garden.
Carey  22:10  It would do really well. Probably.
Brian  22:14  We'll just make the invasives compete with one another to see the we'll just find the most invasive among them, 
Jason  22:20  yeah, if you need suggestions for invasive I have a long list of ones. I've been trying to get rid of rhizomatous, bamboo, privet, kudzu, Japanese bent grass, 
Brian  22:30  Japanese honeysuckle.
Lanny  22:33  It was, sadly, all too easy to find a great list of invasive species. And as Atlanta residents, Kudzu is like, really, our star issue is our jumping off point. 
Jason  22:44  It's like the poster child of invasive plants, 
Lanny  22:46  especially in the South. In the southern United States, you can drive by and you're like, oh, that entire field, this entire mile of freeway, is just covered in kudzu.
Brian  22:57  the plant that ate the south.
Jason  22:59  so maybe kind of winding down, I've got a question for you all about general game design. So you mentioned that this is the first game that you're really taking all the way through development and production, and it's been a learning curve. So for any of our listeners who maybe also be thinking of going down that path, like, what are the major lessons you learned? Maybe, like, top two or three things to pass on to future people to help them along their path, or at least maybe spare them a little bit
Lanny  23:23  of pain. It's a really good question. And I mean, my first recommendation if you are at the beginning of the path is just to put pen to paper, or like, whatever that means for your game, stick things on dice, use pips to make your resources, because it is not going to come out of you perfect. And there was before I started making games, I was like, Oh, I like, need to come up with the full concept before I really, like start. And that is not true. You want to get something out and start, like playing around with it, because the game is going to evolve. I mean, our game Flora VISTA has evolved so much since we started. One of our original concepts was the amount of sun a plant can get was going to be some sort of factor or resource or something. And ultimately, as we started play testing it with ourselves and play testing with our friends, you learned. Okay, this is really fun. This is really important. This mechanic's not really working. This thing is a rule for one card, but it's not a rule for every other card, like, just drop it. There's just so much that you learn just by, like, taking the next step and putting it down. And then my other suggestion, which is not to dissuade anyone in any way, shape or form, is that it takes a while. It just, it sort of takes a while to really go from like concept to the end of the finish line. And Carey alluded to this when we started. We were like, this will be a project that we finish in a year. Here, and we're here three years later, and I'm, there are points where I'm like, Oh, it would have been great if we could have done six months, but that's just like, not even possible in any way, shape or form. You know, you've you've got to do Alpha prototyping, you've got to do beta prototyping. You want to get your actual prototype from the manufacturer that you're going to work with. Because, man, that was such a unique experience, because there were things that looked great on the computer that when we got it in, we were like, Oh, this just does not translate when we print. And so you want to really see it physically in front of you. And then we get to play with people like Brian and show it off to people, and get people interested and excited. So again, it is not to dissuade people in any way, but it is a longer process than you might think, 
Brian  25:46  a marathon, not a sprint, 
Lanny  25:48  exactly, exactly. And sort of when you can reframe that, it sort of makes everything better. Because at the beginning I was like, Oh, we blew through our one year goal right here. And at that point we were still, we were on, like, hand printed stuff that all had the same plant image that really confused everyone. Everyone was like, Wait, not everything is an orchid. And we're like, no, no, that's just a placeholder. We just have not figured out everything at this point. And so actually, our first prototype was on the back of the index cards. So it is, it's really evolved, and you've just sort of got to stay the course and and I think the last thing that I'm going to say is have friends that are willing to do it. And my sweet husband has played this game, probably, aside from Carey and I, more than any other person on this planet. And he is so sweet to like, keep on working through things. And, you know, one of the challenges we gave him at the beginning that he loved was like, how could you break this game? Like, help us figure out the ways in which, like, you know, you create a game to be balanced and replayable. But like, are there things we have not thought of that just totally break all of the core mechanics of the game, and that was a really great lesson too, on like, Okay, what actually doesn't work here and needs to be streamlined and improved.
Brian  27:09  Jason and his wife were my kind play testers, and Jason is an expert in breaking games it's his specialty.
Lanny  27:15  Thank you, Jason. We need you guys. You guys are as important as we are, because if you just create a game in a silo that no one's played, it needs to be played. It needs to be played so that it's smart and it's good and it's replayable. 
Brian  27:30  You need your bug testers, basically, right, your people who are really putting it through its paces and trying to find those weird edge cases.
Jason  27:38  Yeah, we've heard from multiple creators that by the time your game is done, all of your friends and family should be absolutely sick of it and never want
Carey  27:44  to play it again. They probably are. I think one funny thing is, you don't necessarily think about is the rule book. 
Brian  27:51  Oh yeah.
Carey  27:51  And you know, Lanny and I have played so many times we know how to play the game, and then we start to write down the rules, and we're like, 
Brian  27:59  English sucks. That's the problem. 
Carey  28:01  It's like, oh, well, we know how to play this game really well. But how do I yeah, how do I put this in writing so someone else understands? And that's a very different challenge that you run into. And then you also realize, oh, what actually are our rules? Like we change them up so often. Which ones do we actually want to go with? It forces you to make tough decisions about your game, you know, and that's when you rely on your play testers, too, because we ran into this a couple times, like you start designing the game for yourself, which is a fun thing to do, but Lanny and I, you know, we tend to like more medium like heavy games. And Flora VISTA was never meant to be like a really heavy strategy game that takes, you know, hours to play. And so we're like, oh, you know what we need to we need to think about our audience. Maybe, you know, cut back through the difficulty level a little bit, do some more play testing, see what works, and go from there. And, you know, look at other games for inspiration, honestly. Like, how do other games design their rule book? How do they handle the artwork. How do they do their marketing and promotion? Like designing games, that's the fun part. Lanny and I had a great time, I think, doing that, you know, starting out on business cards, iterating. I remember our Excel sheet I was working in Photoshop, and I'm like, I created this macro that would automatically, like, generate 300 cards for us, and we could easily print them out and make changes based on that. 
Brian  29:22  Oh, wow. 
Carey  29:22  But then you realize, okay, well, now we have to figure out how to produce this game, and then we had to figure out how to market this game. Other things we didn't think about about like, you know, we need a trademark for this game.
Lanny  29:32  There are a lot of different hats you get to wear. Yeah, you get to learn what you like and maybe what's a challenge for you. But it was, it's been really cool. I didn't know much about marketing before this game, and it's been a very interesting hat to wear.
Brian  29:46  I've got one more question I was hoping to ask Jason, did you have one more as well? I have one more, but mine's fast, so you go first All right. This is something I want to start doing when we get people on I'm taking inspiration from another podcast I listen to called monster talk. What are some of your favorite games with a Science or Nature theme? Do you have one?
Lanny  30:07  I love wingspan. I love the bird theme. In that I'm one of those people that reads every single bird fact that's on there. And I, I love the map that's on there. And I actually we really wanted to put a map on our cards too, of where it grows. And this was one of the things that we really learned while we were putting everything together. It's like too much information suddenly makes the card like too cluttered, and you can't pick out the information you really need. Pandemic is up there
Brian  30:39  two of our highest scoring games from the podcast. So I we agree with you on both of these. 
Lanny  30:44  I like habitat. 
Brian  30:46  Oh, we'll, write that one down. Don't know that one.
Lanny  30:49  I'm not thinking of the right game. I'm so sorry. I'm thinking of harmonies. Was what I was thinking of.
Brian  30:57  Yes, literally my favorite game of last year. 
Lanny  30:59  Oh, fantastic. I really like Ark Nova. That's like an animal Zoo. And I love, I love a zoo, honestly. 
Brian  31:06  So who doesn't love a zoo? 
Lanny  31:08  Yeah, or an aquarium? Oh, gosh, our aquarium in Atlanta. Love that aquarium.
Brian  31:14  World class, world class, 
Jason  31:15  yes. If you're ever in Atlanta and you can only visit one thing, do not go to the coke Museum. Go to the aquarium. It's much better
Lanny  31:22  100% and you've got to get here before 
Brian  31:25  all the school groups, 
Lanny  31:26  all the school groups, and before our last whale shark goes, we will not get any more whale sharks at the Atlanta aquarium, which is for conservation reasons. But the whale sharks are gorgeous, gorgeous, majestic creatures. And sadly, one of them just passed in the last few months.
Jason  31:45  Yeah, I heard that just old age, basically. 
Jason  31:47  Yeah. What about you? Carey? I think all the games Lanny mentioned wingspan for sure. I'm thinking photosynthesis is a fun game. 
Brian  31:55  Okay, I'm glad to hear that a lot of these games we've done before, so, like, we're not missing big parts of the area,
Carey  32:03  no. And there's a national park style game called trekking that I like to play. Lanny had a pretty good list. Only those are the only two I would add, I think,
Jason  32:11  all right. And then my question is, the mirror of that, what's your favorite plant, either in your game, or just in general?
Carey  32:17  I'll go within the game my favorite plants, the California Poppy that I mentioned earlier. And you can kind of see what some of our favorite plants are in the game based on how many points they're worth. So that's a five point card. That's the highest scoring plant in the game. And I think it's just really interesting. It can be, you know, it's technically edible. Indigenous people used to use it as kind of like a pain reliever, or like a mild sedative, which I think is interesting. It kind of reminds me of The Wizard of Oz thing, where Dorothy kind of falls asleep, even though that's not technically a California Poppy. 
Brian  32:54  That's an Oz Poppy, a magical Poppy.
Jason  32:57  I always thought they were opium puppies, but in
Lanny  33:00  Oz, maybe, probably Oz is a weird place, yeah, but I
Carey  33:04  think it's just a beautiful plant overall. I love orange, and I think poppies do this thing where they'll close their petals at night, and it prevents, kind of like predators or pests from bothering it, and it kind of preserves energy. And that's a cool little future that a plant has
Lanny  33:21  in the game and maybe also in real life. We have a royal Fern card. I love ferns. I think they are so cool and unique, and they're like history on the earth is so unique. You guys probably know more than I do about the classification of ferns, but they are, they sort of function so different from a lot of other plants. I find that so interesting and that it's been around since like prehistoric eras, like is just so cool to me. And then within the game, one of our cards is the royal Fern, and I probably researched about three to five plant facts about every single plant in this game, and I found this one, and was instantly like, this is absolutely going in the game. In Slavic mythology, if you held royal Fern spore clusters, you were said to be able to slay demons and talk to plants. And why? Yeah, I know. And I'm like, Cool. I'm going out to get some royal Fern clusters immediately. 
Brian  34:25  Yeah, you got all those demons to slay, right? 
Lanny  34:28  Right? Exactly. I can live out my Buffy fantasy. I can be a real life druid. It's like, perfect. And I'd be like, a huge fantasy mythology person. So that one, just like, really spoke to me on a core level,
Brian  34:41  yeah, that sounds very D and D, we got to pull that into a campaign. 
Lanny  34:44  I know, right, exactly,
Jason  34:46  all right. Well, I think we're going to wrap it up there. Thank you both for coming on. If people want to look more into far out Fox games or Flora Vista, where should they go?
Carey  34:54  You can google Flora VISTA or go to Flora Vista.faroutfox.com and You can sign up for updates. 
Lanny  35:01  Yep, and we are looking forward to our audience finding the game and backing us on Kickstarter and getting the game in real life. It's going to be a lot of fun. And thank you both for this interview. Thank you Brian for playing with us already, 
Brian  35:16  absolutely
Jason  35:18  well, we're going to call it there. So thank you everyone for listening. Have a great month and happy games
Brian  35:23  and have fun playing dice with the universe. See ya. 
Jason  35:25  This has been the game of the Science Podcast copyright 2025 listeners are free to reuse this recording for any non commercial purpose, as long as credit is given to game in the science this podcast is produced with support from the University of Georgia. All opinions are those of the hosts, and do not imply endorsement by the sponsors. If you wish to purchase any of the games we talked about, we talked about, we encourage you to do so through your friendly local game store. Thank you and have fun playing dice with the universe.
Transcribed by https://otter.ai