Better automated abstraction techniques for imperfect information games, with application to Texas Hold'em poker
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[1] Philip Wolfe,et al. Contributions to the theory of games , 1953 .
[2] Tuomas Sandholm,et al. A Texas Hold'em poker player based on automated abstraction and real-time equilibrium computation , 2006, AAMAS '06.
[3] Tuomas Sandholm,et al. A Competitive Texas Hold'em Poker Player via Automated Abstraction and Real-Time Equilibrium Computation , 2006, AAAI.
[4] David H. Reiley,et al. Stripped-Down Poker: A Classroom Game with Signaling and Bluffing , 2008 .
[5] Kevin B. Korb,et al. Bayesian Poker , 1999, UAI.
[6] J. MacQueen. Some methods for classification and analysis of multivariate observations , 1967 .
[7] David Sklansky,et al. The Theory of Poker , 1999 .
[8] J. Neumann,et al. Theory of Games and Economic Behavior. , 1945 .
[9] Rickard Andersson. Pseudo-Optimal Strategies in No-Limit Poker , 2006, J. Int. Comput. Games Assoc..
[10] Andrew W. Moore,et al. Accelerating exact k-means algorithms with geometric reasoning , 1999, KDD '99.
[11] Peter Bro Miltersen,et al. Computing sequential equilibria for two-player games , 2006, SODA '06.
[12] Terence Conrad Schauenberg,et al. Opponent Modelling and Search in Poker , 2006 .
[13] Tuomas Sandholm,et al. Finding equilibria in large sequential games of imperfect information , 2006, EC '06.
[14] Jonathan Schaeffer,et al. Approximating Game-Theoretic Optimal Strategies for Full-scale Poker , 2003, IJCAI.
[15] Nicholas V. Findler,et al. Studies in machine cognition using the game of poker , 1977, CACM.
[16] B. Stengel,et al. Efficient Computation of Behavior Strategies , 1996 .
[17] F. M. Weida,et al. Traite du Calcul des Probabilites et des ses Applications.@@@Applications aus Jeux de Hazard. , 1941 .
[18] Jonathan Schaeffer,et al. Game-Tree Search with Adaptation in Stochastic Imperfect-Information Games , 2004, Computers and Games.
[19] Aaas News,et al. Book Reviews , 1893, Buffalo Medical and Surgical Journal.
[20] Michael H. Bowling,et al. Optimal Unbiased Estimators for Evaluating Agent Performance , 2006, AAAI.
[21] Bret Hoehn,et al. Effective short-term opponent exploitation in simplified poker , 2005, Machine Learning.
[22] Peter Bro Miltersen,et al. A near-optimal strategy for a heads-up no-limit Texas Hold'em poker tournament , 2007, AAMAS '07.
[23] H. Kuhn. 9. A SIMPLIFIED TWO-PERSON POKER , 1951 .
[24] J. J. Stone,et al. A symmetric continuous poker model , 1960 .
[25] Rufus Isaacs,et al. A Card Game with Bluffing , 1955 .
[26] L. Friedman. Optimal Bluffing Strategies in Poker , 1971 .
[27] Laurence A. Wolsey,et al. Integer and Combinatorial Optimization , 1988 .
[28] L. S. Shapley,et al. 10. A SIMPLE THREE-PERSON POKER GAME , 1951 .
[29] William H. Cutler. An Optimal Strategy for Pot-Limit Poker , 1975 .
[30] Jonathan Schaeffer,et al. Opponent Modeling in Poker , 1998, AAAI/IAAI.
[31] Richard Bellman. On games involving bluffing , 1952 .
[32] Ian Davidson,et al. Speeding up k-means Clustering by Bootstrap Averaging , 2003 .
[33] David M. Kreps,et al. Sequential Equilibria Author ( s ) : , 1982 .
[34] Kevin Burns,et al. Pared-down Poker: Cutting to the Core of Command and Control , 2005, CIG.
[35] Michael L. Littman,et al. Abstraction Methods for Game Theoretic Poker , 2000, Computers and Games.
[36] R BELLMAN,et al. Some two person games involving bluffing. , 1949, Proceedings of the National Academy of Sciences of the United States of America.
[37] Avi Pfeffer,et al. Representations and Solutions for Game-Theoretic Problems , 1997, Artif. Intell..
[38] Michael H. Bowling,et al. Bayes' Bluff: Opponent Modelling in Poker , 2005, UAI 2005.
[39] Jonathan Schaeffer,et al. The challenge of poker , 2002, Artif. Intell..
[40] Kevin Burns,et al. Heads-Up Face-Off: On Style and Skill in the Game of Poker , 2004, AAAI Technical Report.
[41] Donald J. Newman. A Model for “Real” Poker , 1959 .
[42] D. Koller,et al. Efficient Computation of Equilibria for Extensive Two-Person Games , 1996 .
[43] Nathan R. Sturtevant,et al. Prob-Maxn: Playing N-Player Games with Opponent Models , 2006, AAAI.