AI beats professionals
For the first time, an artificial intelligence system has beaten human professionals at a game of Texas hold 'em poker, scientists say.
It is a historic result in artificial intelligence (AI) that has implications far beyond the poker table, from helping make more robust medical treatment recommendations to developing better strategic defence planning.
- DeepStack, created by researchers at the University of Alberta in Canada, bridges the gap between approaches used for games of perfect information - such as chess and Go where players can see everything on the board - with those used for imperfect information games by reasoning while it plays, using "intuition" honed through deep learning to reassess its strategy with each decision.
- Poker has been a long-standing challenge problem in artificial intelligence," said Michael Bowling, professor at the University of Alberta.
- It is the quintessential game of imperfect information in the sense that the players don't have the same information or share the same perspective while they're playing.
- AI researchers have long used parlour games to test their theories because the games are mathematical models that describe how decision-makers interact.
- DeepStack extends the ability to think about each situation during play to imperfect information games using a technique called continual re-solving.
- This allows DeepStack to determine the correct strategy for a particular poker situation by using its "intuition" to evaluate how the game might play out in the near future without thinking about the entire game.
- Thinking about each situation as it arises is important for complex problems like heads-up no-limit hold'em, which has vastly more unique situations than there are atoms in the universe, largely due to players' ability to wager different amounts including the dramatic "all-in."