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Published in:
2012 | OriginalPaper | Chapter
Opponent Modeling in Texas Hold’em Poker
Authors : Grzegorz Fedczyszyn, Leszek Koszalka, Iwona Pozniak-Koszalka
Published in: Computational Collective Intelligence. Technologies and Applications
Publisher: Springer Berlin Heidelberg
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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.