Opponent Modeling in Texas Hold’em Poker

  • Grzegorz Fedczyszyn
  • Leszek Koszalka
  • Iwona Pozniak-Koszalka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7654)


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.


Poker game algorithm artificial intelligence neural network 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Grzegorz Fedczyszyn
    • 1
  • Leszek Koszalka
    • 1
  • Iwona Pozniak-Koszalka
    • 1
  1. 1.Department of Systems and Computer NetworksWroclaw University of TechnologyWroclawPoland

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