Investigating the effectiveness of applying case-based reasoning to the game of Texas Hold'em

Proceedings of the Twentieth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2007

Volumn , Issue , 2007, Pages 417-422

  Rubin, Jonathan ^a   Watson, Ian ^a  

^a UNIVERSITY OF AUCKLAND   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

COMPETITION; GAME THEORY; KNOWLEDGE MANAGEMENT; PROFITABILITY;

ALBERTA'S POKIBOTS; POKER SCENARIOS; SIMBOTS;

CASE BASED REASONING;

EID: 37349072470     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. Billings, D., N. Burch, et al. 2003. Approximating game-theoretic optimal strategies for full-scale poker. Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence.
2. Billings, D., A. Davidson, et al. 2002. The challenge of poker. Artificial Intelligence 134(1-2): 201-240.
3. Billings, D., L. Peña, et al. 1999. Using probabilistic knowledge and simulation to play poker. Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence: 697-703.
4. Dahl, F. A. 2001. A Reinforcement Learning Algorithm Applied to Simplified Two-Player Texas Hold'em Poker. Proceedings of the 12th European Conference on Machine Learning Springer-Verlag.
5. Davidson, A. 2002. Opponent modeling in poker: Learning and acting in a hostile and uncertain environment. Master's thesis, University of Alberta.
6. Korb, K. B., A. E. Nicholson, et al. 1999. Bayesian poker. UAI'99 - Proceedings of the 15th International Conference on Uncertainty in Artificial Intelligence, Sweden: 343-350.
7. Salim, M. and P. Rohwer 2005. Poker Opponent Modeling. Indiana University: Personal communication.
8. Riesbeck, C. and R. Schank 1989. Inside Case-Based Reasoning. Hillsdale, NJ.: Lawrence Erlbaum.
9. Sandven, A. and B. Tessem 2006. A Case-Based Learner for Poker. The Ninth Scandinavian Conference on Artificial Intelligence (SCAI 2006), Helsinki, Finland.
10. Schaeffer, J., D. Billings, et al. 1999. Learning to play strong poker. Proceedings of the ICML-99 Workshop on Machine Learning in Game Playing.
11. Schaeffer, J., J. Culberson, et al. 1992. A world championship caliber checkers program. Artificial Intelligence 53(2-3): 273-289.
12. Sklansky, D. 1994. The Theory of Poker. Las Vegas, NV.: Two Plus Two Publishing.
13. Sklansky, D. and M. Malmuth 1994. Hold'em Poker for Advanced Players. Las Vegas, NV.: Two Plus Two Publishing.
14. Watson, I. 1997. Applying case-based reasoning: techniques for enterprise systems. San Francisco, CA.: Morgan Kaufmann Publishers Inc.