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
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References
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)
Mccurley, P.: An Artificial Intelligence Agent for Texas Hold’em Poker. Dissertation, University of Newcastle upon Tyne, The U.K. (2009)
Forge, A.: NET documentation available at http://code.google.com/p/aforge/
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)
Bishop, C.M.: Pattern Recognition and Machine Learning. Springer (2009)
Davidson, A.: Opponent Modeling in Poker: Learning and Acting in a Hostile and Uncertain Environment. Master’s thesis, University of Alberta, Edmonton, Canada (2002)
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)
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Fedczyszyn, G., Koszalka, L., Pozniak-Koszalka, I. (2012). Opponent Modeling in Texas Hold’em Poker. In: Nguyen, NT., Hoang, K., Jȩdrzejowicz, P. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2012. Lecture Notes in Computer Science(), vol 7654. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34707-8_19
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DOI: https://doi.org/10.1007/978-3-642-34707-8_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34706-1
Online ISBN: 978-3-642-34707-8
eBook Packages: Computer ScienceComputer Science (R0)
