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Opponent Modeling in Texas Hold’em Poker

2012; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-642-34707-8_19

1611-3349

Grzegorz Fedczyszyn, Leszek Koszałka, Iwona Poźniak-Koszałka,

Artificial Intelligence in Games

In this paper a new algorithm for prediction opponent move in Texas Hold'em Poker game is presented. The algorithm is based on artificial intelligence approach – it uses several neural networks, each trained on a specific dataset. The results given by algorithm may be applied to improve players' game. Moreover, the algorithm may be used as a part of more complex algorithm created for supporting decision making in Texas Hold'em Poker.