Opponent Classification in Poker

  • Muhammad Aurangzeb Ahmad
  • Mohamed Elidrisi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Opponent Classification Opponent Modeling Poker 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Muhammad Aurangzeb Ahmad
    • 1
  • Mohamed Elidrisi
    • 1
  1. 1.Department of Computer Science and EngineeringUniversity of Minnesota 

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