Poker Learner: Reinforcement Learning Applied to Texas Hold'em Poker
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Games have always been an area of interest for artificial intelligence, especially because of its simple and well defined rules and the need of complex strategies to assure victory. Several researchers from the area of computer science have dedicated their time to the study of games like Chess or Checkers, obtaining notoriety by developing an artificial player capable of defeating the best human players. In the last decade, Poker has become a worldwide phenomenon of growing popularity, proved by the considerable raise in the number of players on online casinos, making Poker a very profitable i...
Games have always been an area of interest for artificial intelligence, especially because of its simple and well defined rules and the need of complex strategies to assure victory. Several researchers from the area of computer science have dedicated their time to the study of games like Chess or Checkers, obtaining notoriety by developing an artificial player capable of defeating the best human players. In the last decade, Poker has become a worldwide phenomenon of growing popularity, proved by the considerable raise in the number of players on online casinos, making Poker a very profitable industry. For the artificial intelligence research field, Poker has also become an interesting domain due to the game's stochastic and incomplete information nature. Because of these two motives, Poker presents itself as a good platform to develop and test solutions for challenges in the artificial intelligence field, like the treatment of the environment's incomplete information and the possibility of random events present in the same environment.
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