That makes it both a tougher AI challenge and more relevant to many real-world problems involving multiple parties and missing information.Īll of the AIs that displayed superhuman skills at two-player games did so by approximating what's called a Nash equilibrium. But poker is a bigger challenge because it is an incomplete information game players can't be certain which cards are in play and opponents can and will bluff. In those games, all of the players know the status of the playing board and all of the pieces. Games such as chess and Go have long served as milestones for AI research. He and Brown earlier developed Libratus, which two years ago decisively beat four poker pros playing a combined 120,000 hands of heads-up no-limit Texas hold'em, a two-player version of the game. Sandholm has led a research team studying computer poker for more than 16 years. Bots/AI are an important part in the evolution of poker, and it was amazing to have first-hand experience in this large step toward the future." "There were several plays that humans simply are not making at all, especially relating to its bet sizing. "It was incredibly fascinating getting to play against the poker bot and seeing some of the strategies it chose" said Gagliano. Michael "Gags" Gagliano, who has earned nearly $2 million in career earnings, also competed against Pluribus. It was playing some of the best players in the world." "The bot wasn't just playing against some middle of the road pros. ![]() Pluribus registered a solid win with statistical significance, which is particularly impressive given its opposition, Elias said. ![]() It's a matter of execution for humans - to do this in a perfectly random way and to do so consistently. "That's the same thing that humans try to do. ![]() "Its major strength is its ability to use mixed strategies," Elias said last week as he prepared for the 2019 World Series of Poker main event. But Pluribus placed donk bets far more often than the professionals it defeated. It's seen as a weak move that usually doesn't make strategic sense. For instance, most human players avoid "donk betting" - that is, ending one round with a call but then starting the next round with a bet. Pluribus' algorithms created some surprising features into its strategy. "We're elated with its performance and believe some of Pluribus' playing strategies might even change the way pros play the game." "Playing a six-player game rather than head-to-head requires fundamental changes in how the AI develops its playing strategy," said Brown, who joined Facebook AI last year. The ability to beat five other players in such a complicated game opens up new opportunities to use AI to solve a wide variety of real-world problems." "Thus far, superhuman AI milestones in strategic reasoning have been limited to two-party competition. in Carnegie Mellon's Computer Science Department as a research scientist at Facebook AI. "Pluribus achieved superhuman performance at multi-player poker, which is a recognized milestone in artificial intelligence and in game theory that has been open for decades," said Tuomas Sandholm, Angel Jordan Professor of Computer Science, who developed Pluribus with Noam Brown, who is finishing his Ph.D. ![]() In another experiment involving 13 pros, all of whom have won more than $1 million playing poker, Pluribus played five pros at a time for a total of 10,000 hands and again emerged victorious. Each pro separately played 5,000 hands of poker against five copies of Pluribus. The AI, called Pluribus, defeated poker professional Darren Elias, who holds the record for most World Poker Tour titles, and Chris "Jesus" Ferguson, winner of six World Series of Poker events.
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