The complexity of stochastic games
Information and Computation
Fast algorithms for finding randomized strategies in game trees
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Certifying and repairing solutions to large LPs how good are LP-solvers?
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Finding equilibria in large sequential games of imperfect information
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
A Texas Hold'em poker player based on automated abstraction and real-time equilibrium computation
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Optimal Rhode Island Hold'em poker
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 4
Approximating game-theoretic optimal strategies for full-scale poker
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Computing an approximate jam/fold equilibrium for 3-player no-limit Texas Hold'em tournaments
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Games for extracting randomness
Proceedings of the 5th Symposium on Usable Privacy and Security
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Computing equilibria in multiplayer stochastic games of imperfect information
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Artificial Intelligence
Building a no limit texas hold'em poker agent based on game logs using supervised learning
AIS'11 Proceedings of the Second international conference on Autonomous and intelligent systems
Repeated zero-sum games with budget
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
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We analyze a heads-up no-limit Texas Hold'em poker tournament with a fixed small blind of 300 chips, a fixed big blind of 600 chips and a total amount of 8000 chips on the table (until recently, these parameters defined the heads-up endgame of sit-n-go tournaments on the popular Party-Poker.com online poker site). Due to the size of this game, a computation of an optimal (i.e. minimax) strategy for the game is completely infeasible. However, combining an algorithm due to Koller, Megiddo and von Stengel with concepts of Everett and suggestions of Sklansky, we compute an optimal jam/fold strategy, i.e. a strategy that would be optimal if any bet made by the player playing by the strategy (but not bets of his opponent) had to be his entire stack. Our computations establish that the computed strategy is near-optimal for the unrestricted tournament (i.e., with post-flop play being allowed) in the rigorous sense that a player playing by the computed strategy will win the tournament with a probability within 1.4 percentage points of the probability that an optimal strategy (allowing post-flop play) would give.