The Challenge of Poker
- Darse Billings, Department of Computing Science, University of Alberta
- A. Davidson, Department of Computing Science, University of Alberta
- Jonathan Schaeffer, Department of Computing Science, University of Alberta
- Duane Szafron, UofA CS
Poker is an interesting test-bed for artificial intelligence research. It is a game of imperfect information, where multiple competing agents must deal with probabilistic knowledge, risk assessment, and possible deception, not unlike decisions made in the real world. Opponent modeling is another difficult problem in decision-making applications, and it is essential to achieving high performance in poker. This paper describes the design considerations and architecture of the poker program Poki. In addition to methods for hand evaluation and betting strategy, Poki uses learning techniques to construct statistical models of each opponent, and dynamically adapts to exploit observed patterns and tendencies. The result is a program capable of playing reasonably strong poker, but there remains considerable research to be done to play at a world-class level.
Citation
D. Billings, A. Davidson, J. Schaeffer, D. Szafron. "The Challenge of Poker". Artificial Intelligence (AIJ), 134(1-2), pp 201-240, January 2002.Keywords: | Computer poker, Imperfect information, Opponent modeling, Simulations, machine learning, Neural networks |
Category: | In Journal |
BibTeX
@article{Billings+al:AIJ02, author = {Darse Billings and A. Davidson and Jonathan Schaeffer and Duane Szafron}, title = {The Challenge of Poker}, Volume = "134", Number = "1-2", Pages = {201-240}, journal = {Artificial Intelligence (AIJ)}, year = 2002, }Last Updated: April 24, 2007
Submitted by Christian Smith