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International Conference on Social Computing, Behavioral Modeling, and Prediction

SBP 2010: Advances in Social Computing pp 398–405Cite as

Opponent Classification in Poker

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6007))

Abstract

Modeling games has a long history in the Artificial Intelligence community. Most of the games that have been considered solved in AI are perfect information games. Imperfect information games like Poker and Bridge represent a domain where there is a great deal of uncertainty involved and additional challenges with respect to modeling the behavior of the opponent etc. Techniques developed for playing imperfect games also have many real world applications like repeated online auctions, human computer interaction, opponent modeling for military applications etc. In this paper we explore different techniques for playing poker, the core of these techniques is opponent modeling via classifying the behavior of opponent according to classes provided by domain experts. We utilize windows of full observation in the game to classify the opponent. In Poker, the behavior of an opponent is classified into four standard poker-playing styles based on a subjective function.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, University of Minnesota,  

    Muhammad Aurangzeb Ahmad & Mohamed Elidrisi

Authors
  1. Muhammad Aurangzeb Ahmad
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  2. Mohamed Elidrisi
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Editor information

Editors and Affiliations

  1. Department of Sociology, University of Hawaii, 2424 Maile Way, Saunders Hall 237, 956-7234, Honolulu, HI, USA

    Sun-Ki Chai

  2. Air Force Research Laboratory, Rome Research Site, AFRL/RIEF, 525 Brooks Road, NY 13441, Rome, USA

    John J. Salerno

  3. Department of Behavioral and Social Sciences Research, National Institute of Health (NIH), 31 Center Drive, 20892-2027, Bethesda, MD, USA

    Patricia L. Mabry

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Ahmad, M.A., Elidrisi, M. (2010). Opponent Classification in Poker. In: Chai, SK., Salerno, J.J., Mabry, P.L. (eds) Advances in Social Computing. SBP 2010. Lecture Notes in Computer Science, vol 6007. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12079-4_50

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  • DOI: https://doi.org/10.1007/978-3-642-12079-4_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12078-7

  • Online ISBN: 978-3-642-12079-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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