A world championship caliber checkers program
Artificial Intelligence
Using probabilistic knowledge and simulation to play poker
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
A Reinforcement Learning Algorithm Applied to Simplified Two-Player Texas Hold'em Poker
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Approximating game-theoretic optimal strategies for full-scale poker
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
A Memory-Based Approach to Two-Player Texas Hold'em
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
Artificial Intelligence
Similarity-Based retrieval and solution re-use policies in the game of texas hold'em
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
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This paper investigates the use of the case-based reasoning methodology applied to the game of Texas hold'em poker. The development of a CASe-based Poker playER (CASPER) is described. CASPER uses knowledge of previous poker scenarios to inform its betting decisions. CASPER improves upon previous case-based reasoning approaches to poker and is able to play evenly against the University of Alberta's Pokibots and Simbots, from which it acquired its case-bases and updates previously published research by showing that CASPER plays profitably against human online competitors for play money. However, against online players for real money CASPER is not profitable. The reasons for this are briefly discussed.