International Journal of Fuzzy Logic and Intelligent Systems

  • 제10권3호
  • /
  • Pages.170-177
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  • 2010
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  • 1598-2645(pISSN)
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  • 2093-744X(eISSN)
한국지능시스템학회 (Korean Institute of Intelligent Systems)
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A Learning AI Algorithm for Poker with Embedded Opponent Modeling

  • Kim, Seong-Gon (CISE department, University of Florida) ;
  • Kim, Yong-Gi (Dept of Computer Science, Gyeongsang National University)
  • 투고 : 2010.03.15
  • 심사 : 2010.09.07
  • 발행 : 2010.09.30
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초록

Poker is a game of imperfect information where competing players must deal with multiple risk factors stemming from unknown information while making the best decision to win, and this makes it an interesting test-bed for artificial intelligence research. This paper introduces a new learning AI algorithm with embedded opponent modeling that can be used for these types of situations and we use this AI and apply it to a poker program. The new AI will be based on several graphs with each of its nodes representing inputs, and the algorithm will learn the optimal decision to make by updating the weight of the edges connecting these nodes and returning a probability for each action the graphs represent.

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참고문헌

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