Approximating Game-Theoretic Optimal Strategies for Full-scale Poker
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence. Pages 661-667.
Abstract
The computation of the first complete approximations of game-theoretic optimal strategies for fullscale poker is addressed. Several abstraction techniques are combined to represent the game of 2player Texas Hold' em, having size 0(10 18 ), using closely related models each having size 0(10 7 ). Despite the reduction in size by a factor of 100 billion, the resulting models retain the key properties and structure of the real game. Linear programming solutions to the abstracted game are used to create substantially improved poker-playing programs, able to defeat strong human players and be competitive against world-class opponents.
@inproceedings{ijcai2003p97,
title = {Approximating Game-Theoretic Optimal Strategies for Full-scale Poker},
author = {Billings, Darse and Burch, Neil and Davidson, Aaron and Holte, Robert C. and Schaeffer, Jonathan and Schauenberg, Terence and Szafron, Duane},
booktitle = {Proceedings of the Eighteenth International Joint Conference on
Artificial Intelligence, {IJCAI-03}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Georg Gottlob},
pages = {661--667},
year = {2003},
url = {https://ijcai.org/proceedings/2003/97},
}
TY - CPAPER TI - Approximating Game-Theoretic Optimal Strategies for Full-scale Poker AU - Billings, Darse AU - Burch, Neil AU - Davidson, Aaron AU - Holte, Robert C. AU - Schaeffer, Jonathan AU - Schauenberg, Terence AU - Szafron, Duane T2 - Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03 PB - International Joint Conferences on Artificial Intelligence PY - 2003 SP - 661 EP - 667 UR - https://ijcai.org/proceedings/2003/97 ER -Copied
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