An analysis of forward pruning
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations
Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Upper confidence trees with short term partial information
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part I
A double oracle algorithm for zero-sum security games on graphs
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Security and Game Theory: Algorithms, Deployed Systems, Lessons Learned
Security and Game Theory: Algorithms, Deployed Systems, Lessons Learned
Heuristic search applied to abstract combat games
AI'05 Proceedings of the 18th Canadian Society conference on Advances in Artificial Intelligence
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We focus on solving two-player zero-sum extensive-form games with perfect information and simultaneous moves. In these games, both players fully observe the current state of the game where they simultaneously make a move determining the next state of the game. We solve these games by a novel algorithm that relies on two components: (1) it iteratively solves the games that correspond to a single simultaneous move using a double-oracle method, and (2) it prunes the states of the game using bounds on the sub-game values obtained by the classical Alpha-Beta search on a serialized variant of the game. We experimentally evaluate our algorithm on the Goofspiel card game, a pursuit-evasion game, and randomly generated games. The results show that our novel algorithm typically provides significant running-time improvements and reduction in the number of evaluated nodes compared to the full search algorithm.