Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Experiments in search and knowledge
Experiments in search and knowledge
Low overhead alternatives to SSS*
Artificial Intelligence
The History Heuristic and Alpha-Beta Search Enhancements in Practice
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parallel Search of Strongly Ordered Game Trees
ACM Computing Surveys (CSUR)
The design and analysis of algorithms for asynchronous multiprocessors.
The design and analysis of algorithms for asynchronous multiprocessors.
Performance analysis of the technology chess program.
Performance analysis of the technology chess program.
Performance measurement and analysis of certain search algorithms.
Performance measurement and analysis of certain search algorithms.
A bibliography on minimax trees
ACM SIGACT News
New advances in Alpha-Beta searching
CSC '96 Proceedings of the 1996 ACM 24th annual conference on Computer science
AWT: Aspiration with Timer Search Algorithm in Siguo
CG '08 Proceedings of the 6th international conference on Computers and Games
Best-first fixed-depth game-tree search in practice
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
An analysis of decision quality of minimaxing vs. product propagation
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Exploiting graph properties of game trees
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Forward estimation for game-tree search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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Investigation of several algorithms for computing exact minimax values of game trees (utilizing backward pruning) are discussed. The focus is on trees with an ordering similar to that actually found in game playing practice. The authors compare the algorithms using two different distributions of the static values, the uniform distribution and a distribution estimated from practical data. A systematic comparison of using aspiration windows for all of the usual minimax algorithms is presented. The effects of aspiration windows of varying size and position are analyzed. Increasing the ordering of moves to near the optimum results in unexpectedly high savings. Algorithms with linear space complexity benefit most. Although the ordering of the first move is of predominant importance, that of the remainder has only second-order effects. The use of an aspiration window not only makes alpha-beta search competitive, but there also exist dependencies of its effects on certain properties of the trees.