Bot can beat humans in multiplayer hidden-role games(news.mit.edu)
news.mit.edu
Bot can beat humans in multiplayer hidden-role games
https://news.mit.edu/2019/deeprole-ai-beat-humans-role-games-1120
20 comments
I think if I had guessed, I'd have thought this particular hidden role game was easily beaten with AI since the meaningful choices are so limited. Still, it was worth actually proving. I suspect something like one-night werewolf is unbeatable by ai since it's so heavily based on communication, and there's only one a single vote in the game, though..
ONUW harder than Avalon? Yeah I don't think so. While Avalon has ~15 team selections (for something like an average of 60 picks) plus over 100 yes/no votes, and ~20 fail/success votes... ONUW has pretty much no choices at all.
>one-night werewolf is unbeatable
You're asking the wrong question for starters. The AI does need to "beat" the game. It is being measured on whether it's better at the game than humans. And my experience is that most One Night games devolve into a 50/50 guess. An AI would be better at calculating the odds of the two proposed game states that the players can't actually differentiate. So the AI would surely trivially win more than human players.
>one-night werewolf is unbeatable
You're asking the wrong question for starters. The AI does need to "beat" the game. It is being measured on whether it's better at the game than humans. And my experience is that most One Night games devolve into a 50/50 guess. An AI would be better at calculating the odds of the two proposed game states that the players can't actually differentiate. So the AI would surely trivially win more than human players.
Using language is one of the team's future aims. I don't think it would be impossible, since outside of communication for reasoning / deduction purposes, every in-game action can be described in an obvious and unambiguous manner.
Please let me know if I’m mistaken but it seems that, disappointingly, there is no measure of the quality of players, especially considering that the game referenced is a fan-made clone of the physical game. There’s no ladder, MMR, ELO, ec.
So, of course someone who’s played the game 100,000 or even 10 times is likely to beat someone who’s only just played maybe a handful of games. That’s not a bold - or arguably fair-claim to have beaten a majority of players if those players are all brand new —or a minority of those are veterans— which I suspect is likely given the nature of web based games.
So, of course someone who’s played the game 100,000 or even 10 times is likely to beat someone who’s only just played maybe a handful of games. That’s not a bold - or arguably fair-claim to have beaten a majority of players if those players are all brand new —or a minority of those are veterans— which I suspect is likely given the nature of web based games.
It’s interesting that you’re referring to the ai as ‘someone’ and also that people take it for granted that ais can beat most people at most games.
> there is no measure of the quality of players
This is interesting in itself. 10 years ago it would have been very hard to write a program beating a human at a game where we don't know what makes a player better than another.
This is interesting in itself. 10 years ago it would have been very hard to write a program beating a human at a game where we don't know what makes a player better than another.
We do know what makes a player better, it's win rate. What GP is saying is there seems to be no leaderboard or ELO/MMR to really understand how good the AI actually is at the game.
Is this achievement closer to AlphaGo beating Lee Sedol, or is it more like AlphaStar beating a bunch of Bronze league players?
Is this achievement closer to AlphaGo beating Lee Sedol, or is it more like AlphaStar beating a bunch of Bronze league players?
On the other hand, I would bet that this is a small dedicated community. Much like mafia game communities, I would expect this is a dedicated fan group
I would find the opposite an interesting research direction: can we build a game that bots cannot master but humans can.
This comment makes me feel old.
In the 90s, all games were human-mastery only. Even writing a strong checkers AI or Connect4 AI was considered a major accomplishment. Only Tic-Tac-Toe was really bot-perfect.
With AIs winning in Chess, Go, Poker, and more... I guess the kids these days have forgotten how things were like just a few decades ago.
In the 90s, all games were human-mastery only. Even writing a strong checkers AI or Connect4 AI was considered a major accomplishment. Only Tic-Tac-Toe was really bot-perfect.
With AIs winning in Chess, Go, Poker, and more... I guess the kids these days have forgotten how things were like just a few decades ago.
Contests judged on aesthetic merit may be the last bastion of human advantage. Boxing and figure skating are judged like this. Chess and Go aren't, but most commentators seem to find the machine's moves ugly, so perhaps there'll someday be a category of chess judged for elegance and style.
What do you mean by advantage?
Arimaa is a chess variant which was created to be easy for humans to understand but hard for computers.
https://en.wikipedia.org/wiki/Arimaa#Arimaa_Challenge
https://en.wikipedia.org/wiki/Arimaa#Arimaa_Challenge
I doubt bots will ever be able to play Dixit (for low values of "ever")
Here is the game. Face the opposite player so you're looking at them. Goal: Hold a straight face. Person to start smirking or laughing first loses.
Can bots master this game?
Can bots master this game?
Calvinball.
There is a huge gap between playing werewolf-type games and poker. The article seems to imply that by beating one it should be able to beat the other.
Prove it.
Prove it.
As the other poster has listed: the superhuman Poker AI is already built. They extend the poker-AI to play another game here.
Actually, CFR is really interesting, because it calculates an estimation to the Nash Equalibrium and plays theoretically close to optimal in randomized strategies. Its a straightforward concept from a game-theory perspective, but the "estimation to Nash Equalibrium" part is the interesting part. Since a real Nash Equalibrium is too difficult to calculate, it seems like their estimated Nash-Equalibirum is good enough in practice.
Any "game" with a Nash Equalibrium with randomized strategies should benefit from CFR. Which is most games of "bluffing" and hidden information (Poker, Avalon, Pokemon, Magic the Gathering), and even real-world negotiations, diplomacy, business transactions, etc. etc.
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Since CFR has already proven to be superhuman at Poker, the research problem is now in extending this Nash Equalibirum estimate over to other games. IMO, Avalon / Wearewolf games are too simple, AI Researchers should move to Magic: The Gathering or other more complex games like that instead.
Actually, CFR is really interesting, because it calculates an estimation to the Nash Equalibrium and plays theoretically close to optimal in randomized strategies. Its a straightforward concept from a game-theory perspective, but the "estimation to Nash Equalibrium" part is the interesting part. Since a real Nash Equalibrium is too difficult to calculate, it seems like their estimated Nash-Equalibirum is good enough in practice.
Any "game" with a Nash Equalibrium with randomized strategies should benefit from CFR. Which is most games of "bluffing" and hidden information (Poker, Avalon, Pokemon, Magic the Gathering), and even real-world negotiations, diplomacy, business transactions, etc. etc.
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Since CFR has already proven to be superhuman at Poker, the research problem is now in extending this Nash Equalibirum estimate over to other games. IMO, Avalon / Wearewolf games are too simple, AI Researchers should move to Magic: The Gathering or other more complex games like that instead.
No, they extend the counterfactual regret minimization (CFR) algorithm, which is used to play poker, in order to play Avalon.
This is hard for humans to do, and is made interesting by the ample opportunities for intuitive leaps, but I'm not at all surprised that a program would be better at it. It's very easy in these games to incriminate yourself in ways that might go unnoticed by human players but would be incredibly obvious to an agent that's keeping a perfect record of everything that's happened.