Simulating the Evolution of Teamwork 

blobs will starve no matter what you do

All things must pass

This is an accurate simulation of real world populations. Google how many humans die every day lol

The way it's presented in the video better extends when changing the simulation to allow for mutations. Because both offspring can mutate, while if it's a parent child relation only one can mutate.

@@andresmartinezramos7513 , it could just as easily be said that the one that survived chose to change strategies. Both blobs can still have the same odds of mutating.

Math

F

And the perfect house: r o c k

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@@EEEEEEEE E

I was thinking it would be interesting if they made siblings more likely to go together to the tree.

Correlated interaction! One of my favorite parts of evolutionary game theory. If team try to find team, and solo try to find solo (or don't care who they find), then cooperation will evolve so long as the team blobs find each other enough. That point is determined by Hamilton's Rule, and is actually a pretty neat piece of math. It was initially devised to deal with how altruism applies, but because of some game theory shenannigans, it applies here too. On the other hand, if team try to find team, and solo also try to find team (they do better against team than solo blobs), then it's mathematically like there's no correlated interaction at all. Hope that helped!

@@nyphron3109❤️🙏

omg that’d be so cool! the biggest thing I was left wondering, since I’ve also watched the altruism video, is what would happen if the teamwork blobs gave birth to, or were more likely to give birth to, more teamwork blobs. since in the end they all end up with more food, it would mean they’d have a higher population, right?

I just watched that movie yesterday

That's good, I don't need to deal with schizophrenia I just need to do some math

​@@histhoryk2648it's a 2x1 deal

"What if *nobody* goes for the blonde girl?"

@@LeZylox Hey look, we found THAT guy.

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Y'know, it would be interesting to see a harder system where blobs survive if they have 1 food and reproduce for any excess and keep the memory of blobs they met and can communicate in their under-the-same-rock groups, so that tit-for-tat could actually be a thing. For example, a team blob could change its behavior (if beneficial) if it knows that the second blob is solo because this solo blob interacted with another team player from the same rock home the day before, or the other way around.

The key is that evolution *is* repeated interaction. Whether the same individuals ineract, or their descendants, the impact is the same in a stateless situation (no memory of previous interaction to implement tit-for-tat)

Tit for tat definition: The best strategy is to assume cooperation at first. Then if they act one-sided in that interaction then in your next interact you strive to exactly* negate the extra benefit they received from acting one-sided instead of cooperatively. Then then next interaction you assume cooperation again. This strategy performs better then all other strategies invented as long as you can keep track of who you have interacted with previously and whether they acted cooperatively or one-sided that last time. And this same strategy can be observed in nature... though animals arnt dynamic like humans. They cant really switch strategy within the same livespan. Their behavior is formed due to evolution instead. Also worth mentioning that the above is based on perfect information. The optimal strategy has many more features and complexities when there is imperfect information but it still follows this core aim. The extra stuff is just trying to deal with signal error.

Only if the situation isn’t designed to produce a prisoners’ dilemma. If you were an authoritarian regime and wanted to prevent your citizens from gaining power, you’d make it more beneficial for them to turn on one another than to cooperate. See East Germany and the USSR. I’d also watch out for lawmakers and lobbyists doing this in the current age in what we think are liberal democracies.

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in that scenario cooperation would dominate, because the overall rewards among cooperators are so much higher than between fighters.

@@cheshire1right! We might get the neighbourhoods but the cooperative ones would slowly extend.

friendly neighborhoods contain large eyeless birds and reluctant cable guys

Yes, but I think that'd be just like each different world that he created. In a way, he already did a each neighbourhood thing

Only belief in christ

Pretty sure he's already done that

@@sriramkumaran2310Nah - we’re clever enough not to need fairytales to explain this stuff.

​@@oldvlognewtricksyes we all think youre very intelligent, now r/atheism is down the hall to the left

@@doctaterror Who needs to be an atheist to comprehend basic emergent behaviour?

Really cool

Weird that today i was thinking "man i wanna watch sum primer"

*Y E S*

Hmm interesting... -this one kind of simulates charity. -this simulates stealing (obviously) -this is some level of emotion -this somewhat simulates tribalism/the idea that "we are stronger together" -basically simulates smarter stealers -this creates a new "faction" of blobs

That's so difficult to build but it'd be fun. It's either get stuck implementing and experimenting with specifics; or you'd need to find a way to fractally have the game rules modify over time/generations and have ML decision making models for each blob as an agent and let the rest emerge "naturally" and then analyse what emerged to see if you incidentally created for example "traitor blobs who work with each other, but are selfish against team and solo blobs" and what they did.

@@Bozebo ye..

Evolutionary game theory has answers for all those questions! In order: - Altruism can evolve when the ratio of blobs who share is greater than (penalty for sharing / benefit for sharing). That's called Hamilton's Rule. - This wouldn't make that big of a difference mathematically, because it's basically already happening. - That's called Hawk-Dove-Retaliator, and is a super famous game in game theory. Basically, you try to be cooperative, but if your partner attacks/betrays you, you attack them back. It turns out that cooperating can evolve if there are enough retaliators in the population to keep the solos out. But if there aren't enough, the solos will invade. - This one actually isn't classic game theory, but would definitely be interesting. It's basically a more extreme form of teamwork. I expect it wouldn't change much, though. - This would be the opposite of the retaliator from before: they go to cooperate, but betray anyone who cooperates with them. They wouldn't do very good, because they'd kill each other off. - This would be pre-play signalling (or greenbeard effect), which is a known way for cooperation to evolve. Basically, we make signals at each other, and if we both get the signal, then we cooperate. The issue is if the other blobs can learn: then, I could make the signal at you, you'd try to cooperate, but I'd betray you. So how well pre-play signalling works depends heavily on the constraints of the simulation. Hope that helped! Everything there is Google-able, too.

@@nyphron3109 I'm pretty new at evolutionary game theory and this topic is really interesting to me. Thanks for the explanation!

What predator war are you talking about? I'd love to read about it

@@MartianSantas basically all of north american large predators. The books american serengeti and coyote America cover the subject quite well.

Which case would that count as in this video?

@@unaminggaming neither, it's a combo of the two. They would switch between the two when necessary

@@MortonArcheryby predator war are you talking emu war style or world war style Basically is it animals vs humans or animals vs other animals?

Yes, economic simulations would be cool

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ME TOO

ME TOO

ME TOO

My name is Inigo Blobtoya. You killed my father. Prepare to die.

It sounds to me like this situation is one that would intensify whichever strategy has a greater population.

@@Jellylamps Yeah, if they meet they both die, which is worse for whichever there are less of, causing the outnumbered group to die out. Interested what would happen if they start out equal, though.

This is why tit-for-tat is a better strategy, but it means the losing team blob needs to be able to remember the solo blob and/or pass this informs to other team blobs. This is why humans developed language: to gossip and share who in the group was trustworthy or not

@@skreppeknekker Species is irrelevant, all animals are equally likely to gossip.

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epic

Babe wake up a new primer video dropped

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😂

Imagine putting neural networks in blobs, I wonder what strategies would emerge

@@revimfadli4666 Not much. Neural networks suck at game theory when they're playing in pairs.

@@nyphron3109 wait really? How? What kind of network topology and size? Deterministic or stochastic policies?

@@revimfadli4666 it doesn’t matter, which is the interesting part. The issue you have is that the neural networks lack context that living players in game theory intuitively have. I just wrote a paper on this, actually.

@@nyphron3109 interesting, what kind of context? What's the paper title? Can you make context-informed neural networks to fix that? Does that inability apply to evolutionary game theory (where agents don't even need decision making capabilities), or just classic game theory? Can this "intuition" or its analogue emerge in an evolutionary game ecosystem, just like gene-determined behaviour?

Noticed that as well, it's fascinating

idk the moon is pretty iconic.. oh wait that's just ya mum

@@kiraoshiro615779 buried, 3 found

Hiiiiii

@@feeb4966 hiya :D

Sounds like a skill issue

Effect is basically the same, since the aggregate population has the same pressure to change

Hawks get the first strike

0:16 The moment I saw it, I knew there will be comments like these 😅 5:23 He also purposefully referenced Matpat 😂 I will miss Matpat tho :'(

Technically that should end the very need of the game. Because what makes GT simulations of this kind interesting/relevant is that the 2 sides are unable to coordinate. Like the prisoners dilemma is only a dilemma because you don't know what your opponent is going to play. So assuming teamwork is objectively favourable, and the players are able to learn this, then the problem dissolves.

@kayodesalandy That's fair, but I think the interactions and social elements in learning are really interesting to simulate. However, that's probably because I'm on a different wavelength here.

@Aazdremzul oh I definitely agree! Like the more I think about it, what if we simulated it for a situation where selfishness was actually objectively better for the individual, but the diplomat can convince them otherwise? Of course the game gets exponentially more complicated because we need to simulate how selfish blobs interact with that proposition (endogenously determined by some factor/variable) to show that they are influenced by their physical environment. Funnily enough I'm not mathematically inclined, but game theory puzzles as word-logic games still appeal to me.

@kayodesalandy I'm more interested in socio-economics and psychology personally, but I have a deep admiration for design in all facets. I think it's really interesting how math and probability really finds use in both fun concepts like games and insightful ideas used in psychology.

Do not use this as a guide to how people think in social interactions, we are not animals

Yes we are​@@Paint75

@@Paint75 By definition, though, we are. The main difference between these examples and real-world social interactions is that knowing if something is a nash equilibrium in a social situation can be hard to tell because it depends on many many variables (personality of other person/people, the setting, time, history, etc. So in theory this video describes social decision outcomes perfectly, in practice this isn't that useful for it.

@@erylkenner8045 by definition yes we are animals, what i meant is we dont ACT like animals, people do not act like the blobs in this video, wild animals do. Don’t pretend like youre smarter than you are

please dont hog all the mangoes for yourself

This isn't a natural environment, it's a toy model to demonstrate evolutionary game theory

What

Yummers, aint it

haha

I disagree but respect your opinion

@@snazysanz2479 Cool!

i bet you are a conservative/support capitalism

@@Chayanta :D and what are your arguments for this assumption? :)

Wtf does this have to do with anything​@@Chayanta

Update: did not disappoint at all. Awesome video!