Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
On parallel evaluation of game trees
SPAA '89 Proceedings of the first annual ACM symposium on Parallel algorithms and architectures
On the parallel complexity of evaluating game trees
SODA '91 Proceedings of the second annual ACM-SIAM symposium on Discrete algorithms
A parallel game tree search algorithm with a linear speedup
Journal of Algorithms
On the Optimality of Randomized $\alpha$-$\beta$ Search
SIAM Journal on Computing
On the Monte Carlo Boolean decision tree complexity of read-once formulae
Random Structures & Algorithms
Kasparov versus deep blue: computer chess comes of age
Kasparov versus deep blue: computer chess comes of age
Parallel Search of Strongly Ordered Game Trees
ACM Computing Surveys (CSUR)
Large-scale parallelization of alpha-beta search: an algorithmic and architectural study with computer chess
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A class of parallel algorithms for evaluating game trees is presented. These algorithms parallelize a standard sequential algorithm for evaluating AND/OR trees and the &agr;-&bgr; pruning procedure for evaluating MIN/MAX trees. It is shown that, uniformly on all instances of uniform AND/OR trees, the parallel AND/OR tree algorithm achieves an asymptotic linear speedup using a polynomial number of processors in the height of the tree. The analysis of linear speedup using more than a linear number of processors is due to J. Harting. A numerical lower bound rigorously establishes a good speedup for the uniform AND/OR trees with parameters that are typical in practice. The performance of the parallel &agr;-&bgr; algorithm on best-ordered MIN/MAX trees is analyzed.