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Poker as a testbed for machine intelligence research (1998)
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| Venue: | Advances in Artificial Intelligence |
| Citations: | 14 - 2 self |
BibTeX
@INPROCEEDINGS{Billings98pokeras,
author = {Darse Billings and Jonathan Schaeffer and Duane Szafron},
title = {Poker as a testbed for machine intelligence research},
booktitle = {Advances in Artificial Intelligence},
year = {1998},
pages = {1--15},
publisher = {Springer Verlag}
}
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Abstract
For years, games researchers have used chess, checkers and other board games as a testbed for machine intelligence research. The success of world-championship-caliber programs for these games has resulted in a number of interesting games being overlooked. Specifically, we show that poker can serve as a better testbed for machine intelligence research related to decision making problems. Poker is a game of imperfect knowledge, where multiple competing agents must deal with risk management, agent modeling, unreliable information and deception, much like decision-making applications in the real world. The heuristic search and evaluation methods successfully employed in chess are not helpful here. This paper outlines the difficulty of playing strong poker, and describes our first steps towards building a world-class poker-playing program.
Keyphrases
machine intelligence research decision making problem strong poker agent modeling interesting game board game game researcher world-class poker-playing program risk management unreliable information decision-making application evaluation method imperfect knowledge world-championship-caliber program heuristic search real world first step towards
