Multi-player alpha-beta pruning
Artificial Intelligence
Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on uniform random number generation
Pruning algorithms for multi-model adversary search
Artificial Intelligence
Probabilistic opponent-model search
Information Sciences: an International Journal - Heuristic Search and Computer Game Playing
On Pruning Techniques for Multi-Player Games
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Last-branch and speculative pruning algorithms for max
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
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In this paper we introduce a new pruning mechanism, called Similarity Pruning for Probabilistic Opponent-Model (PrOM) Search. It is based on imposing a bound on the differences between two or more evaluation functions. Assuming such a bound exists, we are able to prove two theoretical properties, viz., the bound-conservation property and the bounded-gain property. Using these properties we develop a Similarity-Pruning algorithm. Subsequently we conduct a series of experiments on random game trees to measure the efficiency of the new algorithm. The results show that Similarity Pruning increases the efficiency of PrOM search considerably.