DNA Starts to Learn Poker

  • David Harlan Wood
  • Hong Bi
  • Steven O. Kimbrough
  • Dong-Jun Wu
  • Junghuei Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2340)


DNA is used to implement a simplified version of poker. Strategies are evolved that mix bluffing with telling the truth. The essential features are (1) to wait your turn, (2) to default to the most conservative course, (3) to probabilistically override the default in some cases, and (4) to learn from payoffs. Two players each use an independent population of strategies that adapt and learn from their experiences in competition.


Nash Equilibrium Evolutionary Computation Game Tree Coalition Game Game Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • David Harlan Wood
    • 1
  • Hong Bi
    • 2
  • Steven O. Kimbrough
    • 3
  • Dong-Jun Wu
    • 4
  • Junghuei Chen
    • 2
  1. 1.Computer ScienceUniversity of DelawareNewark
  2. 2.Chemistry and BiochemistryUniversity of DelawareNewark
  3. 3.The Wharton SchoolUniversity of PennsylvaniaPhiladelphia
  4. 4.Bennett S. Lebow College of BusinessDrexel UniversityPhiladelphia

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