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Poker Computer Players

 

The game of poker (or at least most of the variants) is considered to be computationally intractable. However, methods are being developed to at least approximate perfect strategy from the game theory perspective in the heads-up (two player) game, and increasingly good systems are being created for the multi-player or ring game. Perfect strategy has multiple meanings in this context. From a game-theoretic optimal point of view, a perfect strategy is a minimax one that cannot expect to lose to any other player's strategy; however, optimal strategy can vary in the presence of sub-optimal players who have weaknesses that can be exploited. In this case, a perfect strategy would be one that correctly or closely models those weaknesses and takes advantage of them to make a profit. Some of these systems are based on Bayes theorem, Nash equilibrium, Monte Carlo simulation, and Neural networks. A large amount of the research is being done at the University of Alberta by the GAMES group led by Jonathan Schaeffer who developed Poki and PsOpt.

A major part of the skill of live poker games, however, is guessing at the strength of a player's hand by identifying tells made by other players, while concealing one's own. This fundamentally differs from games like chess where all information about the game's current state is public. As a computer would not make any tells, playing against a computer would fundamentally change the nature of the game far more than chess and similar games.

Although you cannot read a computer opponent, playing against computer opponents can still help you sharpen your skills by learning how to count outs and play the percentages. With the advancing technology of artificial intelligence, computer players can be created to incorporate bluffs and other human-like decisions.

 


 

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