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AI Beats Four Top Poker Players

• bko 10y ago
  Does anyone know the technical details of how to train and AI bot for a game like poker? I imagine it's just reinforcement learning where the inputs are the actions of the individual players (hold/fold/raise, timing etc) and the statistical probabilities in terms of expected cards. Train a neural net to predict probability of the opponent's hands and act accordingly. Is it just that the professionals all act similarly enough that the bot can learn based on other players?
  • bcassedy 10y ago
    I'm sure the actual process differs from research group to research group. Here's how one commercially available AI training system claims to work. http://www.pokersnowie.com/about/technology-training.html http://www.pokersnowie.com/about/technology-training.html And they go into some of the problems that stem from how they've abstracted the game here: http://www.pokersnowie.com/about/weaknesses.html http://www.pokersnowie.com/about/weaknesses.html
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• doesnotexist 10y ago
  Andrew Ng posted a comment about this on facebook: "I'm thrilled about Libratus' Poker triumph--this is a huge step for AI. Othello/Checkers/Chess/Go were theoretically solvable with minimax tree search and sheer computation; but poker, which requires bluffing, needs sophisticated modeling of your opponents and new algorithmic principles. CMU's Tuomas Sandholm has also (in a private email) promised to publish their algorithms, which I look forward to. Congrats CMU!!!" https://www.facebook.com/andrew.ng.96/posts/1260889373966967 https://www.facebook.com/andrew.ng.96/posts/1260889373966967
  • andrewprock 10y ago
    I'm surprised that Andrew Ng made this claim. The strategy that was built for Libratus' predecessor did not do sophisticated modeling of the opponents, or use new algorithmic principles. Poker is solved using a very large game tree, just as with the other games. The structure of the tree is modified to support the notion of hidden state, but beyond that it is essentially the same as the other games. The structure for representing hidden nodes was developed in the 1950s by Von Neumann. Most of the algorithmic innovations related to how to update the game tree. My guess is that the primary innovation for the Libratus strategy was that of scale.
    • leeleelee 10y ago
      This was my thought too. Poker is quite "solvable" meaning, whenever you're confronted with a decisions -- there is always a "correct" answer which does not have to depend on the other players' behavior or style. And you can find that answer by simulation, or game trees, and other methods. It's also important to keep in mind that the best AI can still lose, and the worst AI can still win (and everything in between). Poker involves randomness, obviously whereas chess/go/etc does not.
      • mormegil 10y ago
        That depends on what you mean by "correct". Sure, you could theoretically find Nash equilibrium of poker and by playing the equilibrium strategy, you can ensure you won't lose. But that does not mean this is the best strategy to use at a given table against the given opponents, who (being imperfect humans) almost certainly do not play the equilibrium strategy themselves. And, by playing a proper nonequilibrium strategy, suited to the specific players, you can win more.
        • andrewprock 10y ago
          The usual way these games are solved is to create an "abstract" game which is tractable, find the Nash equilibrium, and map state in the real game back to the "abstract" game. In the limit, the solutions for a well designed "abstract" game will converge to that of the real game.
• MaggieL 10y ago
  Surely nobody is surprised? Perfect knowledge of probabilities, no emotion and immune to bluffing.
  • random_rr 10y ago
    Uh... that's a very dismissive comment for quite the breakthrough! Congrats to the human players and the AI team for a great showmatch.
  • throw_away 10y ago
    "Capable of bluffing" would perhaps be the surprising thing.
    • xapata 10y ago
      To "bluff" in this case is defined as putting in more money than would be smart if all cards were played face-up. The AI is easily capable of bluffing and in fact should do so frequently.
  • DennisP 10y ago
    It's not immune to bluffing, it's just better at it than humans are. Bluff too much, and your opponent can just call you whenever he has a strong hand, winning more often than not. Don't bluff enough, and your opponent can fold whenever you bet, knowing you probably do have a strong hand. Find the right balance, and your opponent can't exploit you. With no-limit hold'em this is extremely complicated, and until recently the best humans have always beaten the best bots.
  • sanswork 10y ago
    Nothing is immune to bluffing.
  • jasonwatkinspdx 10y ago
    > immune to bluffing There's no such thing. An algorithm playing straight hand value based on probabilities is more susceptible to bluffing, not less. And this is no limit, where a single hand can swing all the chips. Any poker AI that isn't a loser is going to have some pretty sophisticated modeling of the opponent.
• brilliantcode 10y ago
  it won't be long before we hearing more headlines like: "AI beats top 10 hedge fund managers" to "AI run hedge fund blows up due to black swan event" regardless it's an incredible feat. It really casts questions into what our edge as humans are which is slowly disappearing and we didn't even need to put a brain in a jar and hook it up to a computer....it's deep learning reinforced algorithms that is appearing to outlearn, outthink the best of humans. I just can't emphasize what a monumental period in history we are at. Humans are producing specialized algorithms that learn and hold information about the deep web of relationships between myriads of parameters to produce superior performance than humans. It's almost like we've uncovered ways to automate our intelligence very much like we've been automating human and animal labor in the past couple centuries. So the question is, how does an average joe hacker like me exploit and leverage this wonderful thing called deep learning? I'm not interested in reading PHD papers with advanced calculus. I want to have a map of what AI, ML, DL, NN methodologies to use and when and who to hire based on that. This is no time to be a luddite and don't count on basic income from appeasing the masses anytime soon. Much like people took the most hit in the early rise of industrial revolution, our generation and immediate generation will be hit the hardest.
  • bduerst 10y ago
    >AI beats top 10 hedge fund managers" Hedge funds are already using A.I. successfully. I talked one manager who's team was trying to layer successful individual neural networks into a "bigger brain".
    • deepnotderp 10y ago
      Been there, done that (well kind, of, via several small specialized nets). Actually a pretty good trading strategy, but works better if you actually have capital to use it....
      • sulam 10y ago
        I was under the impression that you need some capital, but not so much that you move the market with your trades. True?
• moosinho 10y ago
  Hmm, why is it surprising that AI is good at poker? The way I see the game is that a bad poker player will just hold a model of his hand in mind. A slightly better one will also hold a model of his opponent's hand. Even better one will also model his opponent's model of himself... and so on recursively. And who's really good at recursion? Computers.
  • wstrange 10y ago
    I tend to agree, but I suppose there is also a bluffing element. How likely is it your opponent is bluffing, based on their past behavior? Should you try and bluff this hand?
  • niketear 10y ago
    People have been trying and failing to do so for decades, the state space of the underlying incomplete information game is absolutely massive.
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• spurgu 10y ago
  Reddit AMA from the live match: https://www.reddit.com/r/IAmA/comments/5qi3i9/we_are_professional_poker_players_currently/ https://www.reddit.com/r/IAmA/comments/5qi3i9/we_are_profess...
• blueside 10y ago
  Unfortunately this fails to impress me, merely because you could theoretically build a terrible AI and still win.
  • TylerE 10y ago
    Just showing your ignorance. That margin of victory over that many hands isn't luck or coincidence. The pros were absolutely dominated.
    • blueside 10y ago
      I disagree and it's not ignorance on my part. Due to the nature of the poker and heavily weighted component of luck, a terrible AI can theoretically win. I am sure the AI they built is a mighty and spectacular achievement, but poker is about the only game I know where the worst player can easily beat the best player. Prove me wrong and I'll happily accept your insult of "ignorance" edit I should have been more clear, as I am extremely impressed with the AI's results of hands over time. I am referring to the context of a standard tournament where the loser is eliminated after losing their chips.
      • jat850 10y ago
        On a hand by hand basis, sure. In freezeout tournaments, yes. In heads-up over 120k hands? No. This was not a lucky win. And I say this speaking as a one-time full time player in a number of formats. Variance does not explain this loss.
      • madenine 10y ago
        "the worst" player might win a few hands, or even beat "the best" player due to luck. They will not be able to consistently beat a better player, especially not professional players. That's what this AI is doing. It didn't beat them once or twice. It beat them consistently over the course of 120,000 hands in a 20 day event. Is it theoretically possible that "the worst" player could do that based entirely on luck? Sure, probably in the same realm as monkeys, typewriters, and Shakespeare.
      • 10y ago
• karmacondon 10y ago
  Does anyone have link to papers about the technology behind Libratus?
  • niketear 10y ago
    the endgame solver used is described in http://www.cs.cmu.edu/~noamb/papers/17-AAAI-Refinement.pdf http://www.cs.cmu.edu/~noamb/papers/17-AAAI-Refinement.pdf the first authors twitter account https://twitter.com/polynoamial/ https://twitter.com/polynoamial/
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• RyanRies 10y ago
  Did I read the article incorrectly, or did it say that the bots creators were feeding it additional data each night before the next day's tournament? If so that defeats the entire purpose, doesn't it?
  • niketear 10y ago
    in what way would that defeat the purpose? the players can also review their days play during the night
    • RyanRies 10y ago
      Yeah... I guess I was just expecting the AI to be more self-learning and self-tuning...
      • 09bjb 10y ago
        It built most of its decision model by playing itself over "trillions of hands", according to Prof. Sandholm. You could almost think of the nightly reviews as a similar process to a human sleeping: we benefit from memory consolidation, pruning, time to reflect, etc. I don't see giving the computer 12 hours a night to do something close to reflection and self-analysis as "cheating," or even very different from what its opponents did over Mexican food each night.
        • kkoomi 10y ago
          The four humans were even "colluding" too.
• jedberg 10y ago
  EDIT: Read below, I am wrong. I clearly didn't know what I was talking about. This is a great achievement in AI, don't get me wrong, but the headline should read, "AI beats the best four poker players we could find who were willing to play for a mere $200K". All the actual best players play for millions and have a reputation to uphold. They would never agree to do this. They four guys they got are pretty good, and could certainly destroy me, but they aren't the best of the best. I'd love to see the bot play in the World Series of Poker for a few million.
  • baq 10y ago
    my understanding is these are some of the best HU players the world has seen. WSOP is a completely different story being a super-large MTT.
  • sanswork 10y ago
    >All the actual best players play for millions and have a reputation to uphold. All these players are high stakes players. I think you're underestimating the fun factor. As for reputation. For a poker player having a reputation as being beatable is a profitable thing to have. >but they aren't the best of the best. Who do you think is? Like how many people do you think rank above this group at HUNL?
    • softawre 10y ago
      I agree, these probably aren't the best. Same as in programming. There are some great programmers that we all know and that are public figures. But the absolute best? Probably making high 7 figures working in a dark room somewhere.
      • sanswork 10y ago
        When it comes to HUNL specialists the best have to be public because there isn't as much action offline as in full ring and MTTs. They aren't the best since I think that probably is safely in Polks hands but they are near the best.
    • 10y ago
• sethbannon 10y ago
  "Each night after the play ended, the Pittsburgh Supercomputing Centre added computations to sharpen the AI's strategy." This sounds more like an "advanced chess" setup, where a human teams up with an AI to play. The title of the article should really be "amateur poker players + AI defeat professional poker players". The real test would be if the AI self-corrected over the length of the tournament, without human intervention.
  • mrob 10y ago
    That's only true if the humans made decisions about what computations to do after each day's play. The computations could have been determined in advance, eg. always run some algorithm to analyze the opponent's play for weaknesses. That's not cheating because the human players get to do the same thing. It's impossible to enforce a "no thinking outside the game room" rule for a multi-day tournament.
    • digler999 10y ago
      I dont think it's "cheating", but it's not just AI that's beating the humans. If operators are allowed to change/tune the AI's algorithm, the human opponent should get to replace himself with another player. or conversely, operators shouldn't be allowed to tweak the AI logic, but if they program the AI to tweak itself, like review its moves and adjust its algorithm automatically, that would be reasonable, then the AI and nothing but the AI is responsible for the victory.
      • stromgo 10y ago
        I don't see why you call it "operator tweaking" even if the computations were determined in advance. You're asking for the poker bot to be scripted to log into the Pittsburgh Supercomputing Centre on its own and run overnight jobs there. That idea sounds extremely brittle and the challenge of making that script reliable has nothing to do with poker.
  • bduerst 10y ago
    "He added that the professionals had been sharing notes and tips in an effort to find weaknesses in the AI's game-play." This doesn't sound like they had the goal of conducting a fully controlled experiment here, but it's still interesting none the less.
• rapfaria 10y ago
  Put it against Negreanu. "Oh you have AJ don't you?"
  • Fuzzwah 10y ago
    Negreanu wouldn't sit HU against the 4 players who played the bot.
    • xapata 10y ago
      Depending on the stakes, of course.
  • thefalcon 10y ago
    I'd watch that Twitch stream. (I've mentioned it elsewhere on here but I still find it strange that they were livestreaming and allowing the pros to interact with the viewing audience during the experiment.)
• eliben 10y ago
  Does the computer-ness of the AI give it advantage in poker w.r.t. counting cards, at which humans are imperfect? Or are humans perfect enough these days?
  • strictnein 10y ago
    There's no counting cards in poker. 52 card shuffled deck each time.
    • npongratz 10y ago
      It's not "counting cards," but to be minimally successful at certain variants like seven card stud, I'd argue one must[0] remember cards that have been folded in the current hand. But certainly in all HE variants (that I'm aware of), counting and remembering is unnecessary. [0] It's necessary, but not sufficient.
• bcassedy 10y ago
  Anyone that's interested in reading a more detailed account of the experiment can do so here: http://www.pokerlistings.com/libratus-poker-ai-smokes-humans-for-1-76m-is-this-the-end-42839 http://www.pokerlistings.com/libratus-poker-ai-smokes-humans... The above article spells out some of the details of the competition. The winrate (14.72bb/100) that the AI achieved over the 120k hand sample is almost certainly not due to luck. It is a huge winrate that most pros have to employ strong game selection techniques to achieve (only play against bad players). Here's a layman's explanation of how a poker AI can be trained: http://www.pokersnowie.com/about/technology-training.html http://www.pokersnowie.com/about/technology-training.html And some details about the weaknesses resulting from how they've abstracted the game: http://www.pokersnowie.com/about/weaknesses.html http://www.pokersnowie.com/about/weaknesses.html
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  • iopq 10y ago
    If it was paying rake like online players do, then that winrate would drop into single digits.
  • fierycatnet 10y ago
    That's pretty impressive, the win rate and amount of hands played. It's certainly not a fluke. At the same time, these 4 pros, I've never heard of them. This AI and organizers should focus on HU specialists. Perhaps even invite players like Negreanu, Ivey, and more recent online pros who've made a fortune. Just don't let Hellmuth to play this machine, it would be a disaster.
    • coltnz 10y ago
      These pros are considered to be top 20 HU online specialists, they would destroy Negreanu and Ivey over the long run at this particular variant (which they have played millions of hands at).
      • marklgr 10y ago
• nojvek 10y ago
  Once this is out, it's going to be have a big impact on online poker games. They way things are going with AI. You have a good algorithm, you can get rich very quickly by being a one man business with hardware rented in AWS. Libratus AI player is modelling it's human counterparts and predicting how they think to outsmart them. When Google started, they got the page rank algorithm and distributed algorithms good enough to run on shitty unreliable cheap computers. They are well on the way to become the world's largest company overtaking Apple someday. Their ad algorithms already know that I am applying for a house loan and are blasting me with ads every fucking page I visit on the Internet. I can totally see Google and Facebook personalizing ads per person and taking advantage of the person's vulnerablaties. Like psychologically modelling them to make them click ads and buy random shit. I can see the start of ultimate God algorithms for marketing. The ability for AI to create drug like experiences for us that we can't stop craving.
  • bamboozled 10y ago
    Not if you have uBlock (http://ublock.org/ http://ublock.org/) installed.
• gexla 10y ago
  Do a search for "long term" in online poker and you'll find that the suggestion for players to determine their level of play based on that "long term" is something like one million hands. That's running 4 tables for full days of poker over a long period of time. For sure it's playing more than 4 players. The probability space of poker is such that 4 competitors isn't going to tell you much. And defining "top" is difficult because "top" may be more celebrity than anything. Everyone has their different objectives. If you are "top" then you sure as didn't get there by building a case history against AI poker bots. Give these guys a chance to adjust, and give them a chance to figure out why the effort to adjust might be worth bothering with.
  • spectrum1234 10y ago
    They played in pairs using mirrored hands and did equity splits when all in. This eliminated not all, but a large amount of variance.
  • halflings 10y ago
    From the article: > A poker-playing AI has beaten four human players in a marathon match lasting 20 days. 20 days seems like plenty of time. No ?
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    • mod 10y ago
      No, the number of hands is relevant here, not the number of days played.
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      • 6nf 10y ago
        They won 14.7 big blinds per 100 hands, playing 120k hands. That's a pretty good win rate and a decent sample size but I don't know how to calculate the p value
• blueside 10y ago
  I'd really be interested in whether intentionally showing your cards instead of mucking them was taken into account by the AI. (e.g. showing your poor hand after a successful bluff)
  • xapata 10y ago
    It was not.
• limbicsystem 10y ago
  Is 6-handed a significantly harder game or is it just (from the computer's point of view) just like playing 5 single games of heads-up?
  • whiskers08xmt 10y ago
    It is much more difficult, as interactions between all of the players usually have to be modeled.
  • snarf21 10y ago
    I would argue that it is significantly harder. In heads up, you can call a bet and see the flop and go from there. In a full table, calling early means you may have to fold to a raise. There is also a much more complicated analysis of the possibility that you are beat. Lots of times I may be in a hand and think I have the original raiser beat but when two other people call before me, the odds are much less that I have all of them beat. I still think the hardest part of poker is the grind. The computer doesn't get bored or tired and play hands it doesn't have a reason too just because they are stuck in a dead streak. Taking a mostly conservative style, you'd expect the computer to out perform over time. It would be curious to know what percentage of the time the players bluffed the AI successfully and vice versa.
  • xapata 10y ago
    No, the actions of players are not independent. For example, if 3 are in the hand and the 1st to act bets the 2nd is less likely to call because of the risk of the 3rd raising. Or was the 2nd only calling instead of raising because they expected the 3rd to raise based on recent aggression?!
  • splonk 10y ago
    It's a significantly harder game. Computing a Nash equilibrium in a 2-player game is relatively straightforward in technique (albeit very computationally expensive in the case of poker). There's several factors that make even 3-player games much more complicated than 2-players. An additional player requires some sort of modeling of the interaction between players, which may not be feasible. For example, Player A may have multiple co-optimal strategies with respect to his own EV, but that affects the EVs for players B and C differently. Player A can choose arbitrarily between these strategies at any frequency, but players B and C can't predict this choice at all. On top of that, Nash equilibrium requires that each player acts independently in their best interest. Teams can be modeled as a single player if necessary, but shifting alliances over the course of a series of hands can't be easily. And on the pure computational complexity side, the state space explodes when you can have more than one opponent in a hand simultaneously. Combinations of players in a hand scales as n!, not n.
• georgeecollins 10y ago
  There is a game humans can still beat machines at with ease, Diplomacy(1). When a machine wins a Diplomacy tournament I know we are finished as anything except pets. 1. https://en.wikipedia.org/wiki/Diplomacy_(game) https://en.wikipedia.org/wiki/Diplomacy_(game)
  • bottled_poe 10y ago
    I'm yet to see a game of Diplomacy every actually end, so that makes it difficult. The only reason this game is difficult for AI is the social interaction required to play the game. If the computer was given a means of making offers and private communication with other players, it would be much like any other game. Rules, game state, probability, goal state, etc.
• afastow 10y ago
  Sounds like the end of online poker is very near. This version required a supercomputer and took a long time to decide its actions but those type of things tend to be quickly improved given enough motivation. Even if poker sites could somehow perfectly detect automated players(which they can't of course), highly skilled poker is profitable enough that some people would be willing to manually execute the actions themselves as directed by the AI.
  • ndh2 10y ago
    Not really. 1v1 is just a small part of poker. Ring games are a whole different beast.
    • afastow 10y ago
      They are more complex for sure but not fundamentally different. I'm amazed the AI managed to win but now that it's happened it's bound to proliferate quickly because there's so much money on the line.
  • 6nf 10y ago
    Online sites have been overrun by bots and cyborgs for years at all but the highest stakes. Most players are already being fleeced by computers online.
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• hooloovoo_zoo 10y ago
  This article http://spectrum.ieee.org/automaton/robotics/artificial-intelligence/ai-learns-from-mistakes-to-defeat-human-poker-players http://spectrum.ieee.org/automaton/robotics/artificial-intel... says 120000 hands were played over the course of more than two weeks. How much of a factor was sheer boredom?
  • thefalcon 10y ago
    It was a factor for sure, especially as the AI would tank (stop and think) quite a bit at predictable spots and so the "Pros" would occasionally use strategies to try to knock out the AI before it would get to that point (they were shooting for a targeted number of hands, so maximizing the hands per hour is to the Pro's benefit). That said, they still had both money and pride on the line, and at least one Pro insisted that he was genuinely doing everything he could to try to win, despite the boredom and desire to be done with it.
• xapata 10y ago
  I suspect Libratus' overbet frequency is overfit to this particular reduced-variance game format. In a normal game, the opponent doesn't take chips off the table after winning a hand and might stand up at any moment. It's hard to know how much that affected the strategy, but in the Reddit thread, the human players said the overbet frequency was what they were most surprised by.
  • 6nf 10y ago
    Maybe overbetting is better EV and humans just don't know it yet. It will be interesting to see if this changes the game at the higher stakes Heads Up tables
    • xapata 10y ago
      Yes, but expected value isn't everything. A good investor considers the ratio of expected return to variance of return. In a normal game, the variance on an overbet is enormous and therefore the denominator of its Sharpe ratio [0] is large and drives the value (or should I say "score" so as not to get confused with "expected value"?) of that action down. You'd happily go all-in pre-flop AA vs KK. On the other hand if you got 4-bet pre-flop by a 22 and you're holding AK, you might ask, "Check it down?" This is assuming the opponent really likes small pocket pairs and will call an all-in, etc. [0] https://en.wikipedia.org/wiki/Sharpe_ratio https://en.wikipedia.org/wiki/Sharpe_ratio
      • 6nf 10y ago
        > you might ask, "Check it down?" In a heads up game? Really? "Check it down?" ???
        • xapata 10y ago
          The example applies more to a ring game, where you might be going after a particular fish and don't want to get involved with a better player. Still, I think it illustrates the principle of trying to keep the variance down. Also, if you're first to act on the next round, it might be worth asking, even if you don't think they'll agree.
• nippples 10y ago
  Can someone clarify why exactly is this being presented as more impressive than beating Chess masters or even Go masters? People talk a lot about number of states in poker, but the hand and visible cards can be easily (to a statitician) reduced to a scalar "probability of having the best hand". At least in terms of crunching the possibility tree this should be a far less computationally intensive challenge.
  • roenxi 10y ago
    What struck me looking at the AlphaGo papers was how human its algorithms were - it was basically doing what a highly orthadox human player would do (pick some moves that look interesting, read as deeply as possible) and then scaling up with a completely inhuman thoroughness and accuracy. At this stage, AI wins in competitive games simply will not impress me. From here it may simply be a tour of force showing the breadth of fields AI can dominate in. After that enthusiastic agreement; poker wins are evidence for the laypeople of something I suspect most people in AI research or game theory already know - a human bluffing isn't a magic advantage in a fair game. The AI can outperform on fundamentals.
  • 6nf 10y ago
    The game of poker differs from Go and Chess in that poker players deal with incomplete information and therefore a successful strategy has to include randomness. If you are dealt AA under the gun, you can't just raise 100% of the time, you have to play a mixture of different moves, perhaps raise big 80% of the time, raise small 10% of the time and limp in 10% of the time (for example). With Go or Chess you can just play the best move in each particular situation and you will not lose. It's just a different kind of game
• doug1001 10y ago
  The University of Alberta bot has been beating top pros at limit hold'em for over 10 years. no-limit and tournament play were deliberately placed outside the scope of their poker-bot projects--at least during the period of time i was following it which was approx. 2004 - 2010. anyone know if the CMU team trained their rig on these variants?
• snksnk 10y ago
  This article is related to no-limit heads-up, which requires a very different style of play than no-limit full ring. Full ring would be significantly more difficult to beat by AI. So the title leaves out some very important information. I am not surprised they beat heads-up; I would have expected it sooner.
• wslh 10y ago
  Could someone explain how Poker is more challenging that games like Go? Please eli5.
  • adamlett 10y ago
    I'm not qualified to give a comprehensive answer, but I would have to imagine that it partly has to do with the fact that poker is a game of partial information. In Go or Chess the current state of the game is known. In poker, you don't know what cards your opponent hold, so you have to assign probabilities based on previous actions, and simulate many different scenarios. Another part has to do with the fact that both you and your opponent have surprisingly many legal "moves" at each turn. because not only must you decide to fold, call or bet, but if you bet, you also have to decide how much.