Searching game trees under a partial order
نویسندگان
چکیده
منابع مشابه
Searching Informed Game Trees
Well-known algorithms for the evaluation of the minimax function in game trees are alpha-beta Knuth] and SSS* Stockman]. An improved version of SSS* is SSS-2 Pijls-1]. All these algorithms don't use any heuristic information on the game tree. In this paper the use of heuristic information is introduced into the alpha-beta and the SSS-2 algorithm. Extended versions of these algorithms are presen...
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We present a new parallel game-tree search algorithm. Our approach classifies a processor’s available work as either mandatory (necessary for the solution) or speculative (may be necessary for the solution). Due to the nature of parallel game tree search, it is not possible to keep all processors busy with mandatory work. Our algorithm ER allows potential speculative work to be dynamically orde...
متن کاملSearching Game Trees in Parallel Using SSS
PARSSS* is a parallel formulation of SSS* that is suitable for shared-memory multiprocessor systems. It is based on the distributed tree search paradigm of Ferguson and Korf. The main difficulty in parallelizing SSS* lies in achieving proper coordination between processes running on different subtrees of the game tree. This has been resolved in PARSSS* by the use of a shared array which maintai...
متن کاملPS*, a new Algorithm for Searching Game Trees
A new sequential tree searching algorithm (PS*) is presented. Based on SSS*, Phased Search (PS*) divides each MAX node into k partitions, which are then searched in sequence. By this means two major disadvantages of SSS*, storage demand and maintenance overhead, are significantly reduced, although the corresponding increase in nodes visited is less apparent even in the random tree case. The per...
متن کاملMaximizing the chance of winning in searching Go game trees
The current global selective search and decomposition search in Go typically back up territory scores. This approach is inherently flawed. We propose a new strategy of backing up ‘‘chance of winning’’. We show how an evaluation function on the chance of winning can be constructed. Also we develop a probabilistic combinatorial game model and an algorithm for decomposition search to work with pro...
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ژورنال
عنوان ژورنال: Artificial Intelligence
سال: 1996
ISSN: 0004-3702
DOI: 10.1016/0004-3702(94)00085-9