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)

Abstract

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.

Keywords

Poker game algorithm artificial intelligence neural network 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Van der Kleij, A.A.J.: Monte Carlo Tree Search and Opponent Modeling through Player Clustering in no-limit Texas Hold’em Poker. University of Groningen, The Netherlands (2010)Google Scholar
  2. 2.
    Mccurley, P.: An Artificial Intelligence Agent for Texas Hold’em Poker. Dissertation, University of Newcastle upon Tyne, The U.K. (2009)Google Scholar
  3. 3.
    Forge, A.: NET documentation available at http://code.google.com/p/aforge/
  4. 4.
    Xhemali, D., Hinde, C.J., Stone, R.G.: Naïve Bayes vs. Decision Trees vs. Neural Networks in the Classification of Training Web Pages. University Loughborough, Leicestershire (2009)Google Scholar
  5. 5.
    Bishop, C.M.: Pattern Recognition and Machine Learning. Springer (2009)Google Scholar
  6. 6.
    Davidson, A.: Opponent Modeling in Poker: Learning and Acting in a Hostile and Uncertain Environment. Master’s thesis, University of Alberta, Edmonton, Canada (2002)Google Scholar
  7. 7.
    Davidson, A., Billings, D., Schaeffer, J., Szafron, D.: Improved Opponent Modeling in Poker. In: Proceedings of International Conference on Artificial Intelligence, ICAI 2000, Las Vegas, Nevada, The U.S., pp. 1467–1473 (2000)Google Scholar
  8. 8.

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

Personalised recommendations