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International Workshop on DNA-Based Computers

DNA 2001: DNA Computing pp 92–103Cite as

DNA Starts to Learn Poker

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2340))

Abstract

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.

Partially supported by NSF Grant No. 9980092 and DARPA/NSF Grant No. 9725021.

Partially supported by NSF Grant No. 9980092

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Author information

Authors and Affiliations

  1. Computer Science, University of Delaware, Newark, DE, 19716

    David Harlan Wood

  2. Chemistry and Biochemistry, University of Delaware, Newark, DE, 19716

    Hong Bi & Junghuei Chen

  3. The Wharton School, University of Pennsylvania, Philadelphia, PA, 19104

    Steven O. Kimbrough

  4. Bennett S. Lebow College of Business, Drexel University, Philadelphia, PA, 19104

    Dong-Jun Wu

Authors
  1. David Harlan Wood
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  2. Hong Bi
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  3. Steven O. Kimbrough
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  4. Dong-Jun Wu
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  5. Junghuei Chen
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Editor information

Editors and Affiliations

  1. Department of Mathematics, University of South Florida, 4202 E. Fowler A. PHY 114, Tampa, FL, 33620, USA

    Nataša Jonoska

  2. Department of Chemistry, New York University, New York, NY, 10003, USA

    Nadrian C. Seeman

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© 2002 Springer-Verlag Berlin Heidelberg

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Wood, D.H., Bi, H., Kimbrough, S.O., Wu, DJ., Chen, J. (2002). DNA Starts to Learn Poker. In: Jonoska, N., Seeman, N.C. (eds) DNA Computing. DNA 2001. Lecture Notes in Computer Science, vol 2340. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48017-X_9

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  • DOI: https://doi.org/10.1007/3-540-48017-X_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43775-8

  • Online ISBN: 978-3-540-48017-4

  • eBook Packages: Springer Book Archive

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