Evolution of Counter-Strategies: Application of Co-evolution to Texas Hold'em Poker

被引:3
|
作者
Thompson, Thomas [1 ]
Levine, John [1 ]
Wotherspoon, Russell [1 ]
机构
[1] Univ Strathclyde, Strathclyde Planning Grp, Glasgow G1 1XH, Lanark, Scotland
关键词
D O I
10.1109/CIG.2008.5035616
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Texas Hold'em Poker is similar to other poker variants in that our decision process is controlled by outside factors as much as the cards themselves. Factors such as our seating position, stack size, the stage of the tournament and prior bets can strongly influence a players decision to bet or fold on a given hand of cards. Previous research has explored the use of these factors as means of betting influence through use of a genetic algorithm applied in an evolutionary learning process. However in this previous work, the evolved player performed against scripted opponents at the table. In this paper we describe a co-evolutionary approach where all players on the table are part of the learning process. Results vary wildly between simulations, with further analysis showing that the ability to create robust strategies is difficult given the adversarial dynamic of the game. Despite this, agents are still capable of adhering to guidelines recommended in expert literature.
引用
收藏
页码:16 / 22
页数:7
相关论文
共 50 条
  • [32] Evolution and co-evolution of regional innovation processes
    Fritsch, Michael
    Kudic, Muhamed
    Pyka, Andreas
    REGIONAL STUDIES, 2019, 53 (09) : 1235 - 1239
  • [33] Evolution and co-evolution of individuals and groups in environment
    Rouchier, J
    Barreteau, O
    Bousquet, F
    Proton, H
    INTERNATIONAL CONFERENCE ON MULTI-AGENT SYSTEMS, PROCEEDINGS, 1998, : 254 - 260
  • [34] Co-evolution of new immunotherapeutics and anti-infective strategies
    Doerner, Thomas
    Burmester, Gerd R.
    CURRENT OPINION IN RHEUMATOLOGY, 2009, 21 (03) : 203 - 204
  • [35] Patent vs. open source: A classroom activity using Texas Hold'em poker
    Picault, Julien
    INTERNATIONAL JOURNAL OF MANAGEMENT EDUCATION, 2020, 18 (02):
  • [36] A reinforcement learning algorithm applied to simplified two-player Texas Hold’em poker
    Dahl, Fredrik A.
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2001, 2167 : 85 - 96
  • [37] Measuring and Evaluating the Potential Addiction Risk of the Online Poker Game Texas Hold'em No Limit
    Clement, Reiner
    Goudriaan, Anneke E.
    van Holst, Ruth J.
    Molinaro, Sabrina
    Moersen, Chantal
    Nilsson, Thomas
    Parke, Adrian
    Peren, Franz W.
    Rebeggiani, Luca
    Stoever, Heino
    Terlau, Wiltrud
    Wilhelm, Michele
    GAMING LAW REVIEW-ECONOMICS REGULATION COMPLIANCE AND POLICY, 2012, 16 (12): : 713 - 728
  • [38] The Poker Boom: Can Casinos Cash-in on Low-Stakes Texas Hold'Em?
    McGowan, Richard A.
    GAMING LAW REVIEW-ECONOMICS REGULATION COMPLIANCE AND POLICY, 2010, 14 (07): : 525 - 531
  • [39] Roles of domain knowledge and working memory capacity in components of skill in Texas Hold'Em poker
    Meinz, Elizabeth J.
    Hambrick, David Z.
    Hawkins, Carlee Beth
    Gillings, Alison K.
    Meyer, Brett E.
    Schneider, Joshua L.
    JOURNAL OF APPLIED RESEARCH IN MEMORY AND COGNITION, 2012, 1 (01) : 34 - 40
  • [40] Fifty years of co-evolution and beyond: integrating co-evolution from molecules to species
    Carmona, Diego
    Fitzpatrick, Connor R.
    Johnson, Marc T. J.
    MOLECULAR ECOLOGY, 2015, 24 (21) : 5315 - 5329