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The bot bluffs, and understands that when its opponent bets it might be a bluff. I would consider that to be strategic behavior. The fact that its strategy is d

The bot bluffs, and understands that when its opponent bets it might be a bluff. I would consider that to be strategic behavior. The fact that its strategy is determined by a mathematical process doesn't change that in my opinion.

slg 7y ago
"Strategic" is probably the wrong word, but I think there is a valid question here regarding the approach the AI is taking. One of the key things for a good poker player is having the ability to adapt and adjust their strategy depending on how others at the table are playing. Sometimes you can have the exact same cards in the exact same position and in one game it is smart to fold and in another game it is smart to raise. From the description in the article, it doesn't appear that this AI takes those ebbs and flows into consideration. Instead it seems to play "purely mathematically optimally on expected value" that was honed through trillions of simulations. There is a cliche about how poker is about playing your opponents and not the cards. Is this AI is only focusing on its cards and ignoring its opponents?
- noambrown 7y ago
  The AI doesn't adapt to the opponents, and that's still an interesting challenge for AI research. That said, at the end of the day, it was making quite a bit of money playing against elite human pros. I think that suggests the cliche is, at least in part, wrong.
  - slg 7y ago
    Making "quite a bit of money" still leaves open the possibility that the AI is leaving a lot of money on the table by not taking opponents into consideration. Also I would be curious to see how it performs against people that aren't "elite human pros". Would this AI win at a higher rate in a game against average recreational players compared to the rate a pro would win? Lastly it is also possible that the pros simply didn't have enough time to adapt to the AI which would be extra important considering the AI plays unlike humans and therefore is harder to predict.
    - noambrown 7y ago
      I think the bot would make a lot of money playing against average recreational players, but it's absolutely true that if you can exploit bad players' weaknesses, then you can make more money than what the bot would earn. We played 10,000 hands over 12 days in the 5 humans + 1 AI experiment. That's quite a long time, and there's no indication that they even began to uncover any weaknesses in that time period. So I'm fairly confident the AI is robust to exploitation, and I think that's a very important quality to have in any AI system.
      - hajile 7y ago
        There was an interesting IRL poker game a few years ago. The player who was running behind started going all in on every hand without even looking at their hand (with a huge amount of success). Out of curiosity, how does a bot deal with oddities things like this?
        deleted 7y ago
        [deleted]
        bostik 7y ago
        This is a solved problem. Open-shoving is a feature of sit-n-gos, so of course people have simulated these and compiled so called "pushbot tables". The parameters are basically pot size and winning probabilities against a random hand. While this particular bot may not have those programmed in, a more powerful variant eventually will.
      - slg 7y ago
        That 10,000 total hands number isn't particularly meaningful on the point of adaptability because the humans aren't sharing information with each other. The important number is how many hands each individual human played against the AI. Another question would be whether the pros knew which player was the AI? Because if they didn't, you are basically throwing a modified Turing Test against the pros before they can even begin to try to find tendencies in the AI. Predicting opponents is a huge part of how people play poker. If the AI plays unlike any human, pros are at huge disadvantage against an AI compared to how they would fair against a similarly skilled but more traditional human player. None of this is meant to diminish what you all accomplished, I'm just highlighting areas of poker in which this AI would be less successful than humans even if it is more successful overall.
b_tterc_p 7y ago
It does bluff, but that’s not my point. My issue is that it bluffs without consideration of its opponent. High level strategic play of most games is about adapting to your opponents play. This bot does not do that. It is secretly a giant lookup table of game state to response. In the case of poker, it appears that adaptability is not as good as pure mathematical optimization. Humans can adapt their strategy, but it’s basically just worse regardless because this thing has cracked the code. I’m surprised that you managed to beat pros without adaptability. It’s pretty impressive and says a lot about how we define strategy. If human adaptability is just not as good as machine optimality across all games, we could imagine discovering that an adaptable poker AI can’t outperform this one. It raises a whole lot of interesting questions because lots of criticism towards something like Starcraft AI is that it is strategically stupid and doesn’t adapt. Now the Starcraft Ai is admittedly kind of stupid now, but we may hit a wall on its creativity simply because creativity is, despite human intuition, a dumb idea.
- Cybiote 7y ago
  If you think about it, any AI that's stopped learning and is now efficiently doing pattern matching or pattern completion (assuming memory and attractor states), instead of running a complex search, is arguably a fancy lookup table hashed by similarity. This includes humans. In other words, lookup table isn't the slight most think it is. But the bot does do real time search so it's not "merely doing" a look-up. Because of how Poker is not sub-game solveable (it is not possible to self-locate within the tree), this bot's play has to get into its opponent's mindspace in a sense. To not be exploitable, it essentially has to infer the other player(s) hidden state and paths from observed actions. This isn't something I've seen in Dota, Starcraft, Chess, Go bots. It's true that it doesn't learn online to find exploitable patterns of other players, but doing this without also making yourself exploitable in turn is a very difficult other problem. Low exploitable near optimal play according to game theoretic notions is considered strategy. While you're correct that online learning is powerful and something machines are not currently good at (in complex spaces), you can avoid being exploited without learning if your experience is rich enough and you know how infer what your opponent is trying to do and anticipate them. I'd argue this lineage of poker bots are the closest to playing that way of the major game playing bots.

slg 7y ago

"Strategic" is probably the wrong word, but I think there is a valid question here regarding the approach the AI is taking. One of the key things for a good poker player is having the ability to adapt and adjust their strategy depending on how others at the table are playing. Sometimes you can have the exact same cards in the exact same position and in one game it is smart to fold and in another game it is smart to raise. From the description in the article, it doesn't appear that this AI takes those ebbs and flows into consideration. Instead it seems to play "purely mathematically optimally on expected value" that was honed through trillions of simulations. There is a cliche about how poker is about playing your opponents and not the cards. Is this AI is only focusing on its cards and ignoring its opponents?

noambrown 7y ago
The AI doesn't adapt to the opponents, and that's still an interesting challenge for AI research. That said, at the end of the day, it was making quite a bit of money playing against elite human pros. I think that suggests the cliche is, at least in part, wrong.
- slg 7y ago
  Making "quite a bit of money" still leaves open the possibility that the AI is leaving a lot of money on the table by not taking opponents into consideration. Also I would be curious to see how it performs against people that aren't "elite human pros". Would this AI win at a higher rate in a game against average recreational players compared to the rate a pro would win? Lastly it is also possible that the pros simply didn't have enough time to adapt to the AI which would be extra important considering the AI plays unlike humans and therefore is harder to predict.
  - noambrown 7y ago
    I think the bot would make a lot of money playing against average recreational players, but it's absolutely true that if you can exploit bad players' weaknesses, then you can make more money than what the bot would earn. We played 10,000 hands over 12 days in the 5 humans + 1 AI experiment. That's quite a long time, and there's no indication that they even began to uncover any weaknesses in that time period. So I'm fairly confident the AI is robust to exploitation, and I think that's a very important quality to have in any AI system.
    - hajile 7y ago
      There was an interesting IRL poker game a few years ago. The player who was running behind started going all in on every hand without even looking at their hand (with a huge amount of success). Out of curiosity, how does a bot deal with oddities things like this?
      - deleted 7y ago
        [deleted]
      - bostik 7y ago
        This is a solved problem. Open-shoving is a feature of sit-n-gos, so of course people have simulated these and compiled so called "pushbot tables". The parameters are basically pot size and winning probabilities against a random hand. While this particular bot may not have those programmed in, a more powerful variant eventually will.
    - slg 7y ago
      That 10,000 total hands number isn't particularly meaningful on the point of adaptability because the humans aren't sharing information with each other. The important number is how many hands each individual human played against the AI. Another question would be whether the pros knew which player was the AI? Because if they didn't, you are basically throwing a modified Turing Test against the pros before they can even begin to try to find tendencies in the AI. Predicting opponents is a huge part of how people play poker. If the AI plays unlike any human, pros are at huge disadvantage against an AI compared to how they would fair against a similarly skilled but more traditional human player. None of this is meant to diminish what you all accomplished, I'm just highlighting areas of poker in which this AI would be less successful than humans even if it is more successful overall.

b_tterc_p 7y ago

It does bluff, but that’s not my point. My issue is that it bluffs without consideration of its opponent. High level strategic play of most games is about adapting to your opponents play. This bot does not do that. It is secretly a giant lookup table of game state to response. In the case of poker, it appears that adaptability is not as good as pure mathematical optimization. Humans can adapt their strategy, but it’s basically just worse regardless because this thing has cracked the code. I’m surprised that you managed to beat pros without adaptability. It’s pretty impressive and says a lot about how we define strategy. If human adaptability is just not as good as machine optimality across all games, we could imagine discovering that an adaptable poker AI can’t outperform this one. It raises a whole lot of interesting questions because lots of criticism towards something like Starcraft AI is that it is strategically stupid and doesn’t adapt. Now the Starcraft Ai is admittedly kind of stupid now, but we may hit a wall on its creativity simply because creativity is, despite human intuition, a dumb idea.

Cybiote 7y ago
If you think about it, any AI that's stopped learning and is now efficiently doing pattern matching or pattern completion (assuming memory and attractor states), instead of running a complex search, is arguably a fancy lookup table hashed by similarity. This includes humans. In other words, lookup table isn't the slight most think it is. But the bot does do real time search so it's not "merely doing" a look-up. Because of how Poker is not sub-game solveable (it is not possible to self-locate within the tree), this bot's play has to get into its opponent's mindspace in a sense. To not be exploitable, it essentially has to infer the other player(s) hidden state and paths from observed actions. This isn't something I've seen in Dota, Starcraft, Chess, Go bots. It's true that it doesn't learn online to find exploitable patterns of other players, but doing this without also making yourself exploitable in turn is a very difficult other problem. Low exploitable near optimal play according to game theoretic notions is considered strategy. While you're correct that online learning is powerful and something machines are not currently good at (in complex spaces), you can avoid being exploited without learning if your experience is rich enough and you know how infer what your opponent is trying to do and anticipate them. I'd argue this lineage of poker bots are the closest to playing that way of the major game playing bots.