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Parallel Minimax Game-Tree Searching

by Van-Dat Cung
"... p'erimentaux, obtenus sur une SEQUENT BALANCE 8000 (10 processeurs) en utilisant des arbres de jeux simul'es, confirment que les meilleures acc'el'erations sont obtenues pour un degr'e k proche du facteur de branchement effectif b 1=2 . Nous 'etudions actuellement l&a ..."
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, such as two-person game-trees. The main previous studies on this area are analyzed and classified according to three techniques of parallelization used : parallelization of processing an individual node, decomposition of the game-tree, and division of the searching range. A new parallel algorithm is presented

On Minimax Game Tree Search Pathology and Node-Value Dependence

by Liwu Li, T. A. Marsl , 1990
"... Here we are concerned with the mysterious phenomenon of minimax game-tree search pathology, where it appears and how it happens. It is commonly believed that the strategy of searchingdeeper for computer game-playing programs can enhance the accuracy of position evaluation and increase the possibilit ..."
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Here we are concerned with the mysterious phenomenon of minimax game-tree search pathology, where it appears and how it happens. It is commonly believed that the strategy of searchingdeeper for computer game-playing programs can enhance the accuracy of position evaluation and increase

A study of decision error in selective game tree search

by Keh-hsun Chen - Information Sciences , 2001
"... In this paper, we study decision errors caused by the omission of part of the legal candidate moves and the inaccuracy of static evaluation in a selective minimax game tree search. Error upper bounds are presented in Section 2. A simple game tree model, which captures some basic characteristics of t ..."
Abstract - Cited by 5 (2 self) - Add to MetaCart
In this paper, we study decision errors caused by the omission of part of the legal candidate moves and the inaccuracy of static evaluation in a selective minimax game tree search. Error upper bounds are presented in Section 2. A simple game tree model, which captures some basic characteristics

A new paradigm for minimax search

by Aske Plaat, Jonathan Schaeffer, Wim Pijls, Arie de Bruin , 1994
"... This paper introduces a new paradigm for minimax game-tree search algorithms. MT is a memory-enhanced version of Pearl's Testprocedure. By changing the way MT is called, a number of best-first game-tree search algorithms can be simply and elegantly constructed (including SSS*). Most of the asse ..."
Abstract - Cited by 14 (10 self) - Add to MetaCart
This paper introduces a new paradigm for minimax game-tree search algorithms. MT is a memory-enhanced version of Pearl's Testprocedure. By changing the way MT is called, a number of best-first game-tree search algorithms can be simply and elegantly constructed (including SSS*). Most

A New Computational Approach to The Game of Go

by Julian Churchill, Richard Cant, David Al-dabass
"... This paper investigates the application of neural network techniques to the creation of a program that can play the game of Go with some degree of success. The combination of soft AI, such as neural networks, and hard AI methods, such as alpha-beta pruned minimax game tree searching, is attempted to ..."
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This paper investigates the application of neural network techniques to the creation of a program that can play the game of Go with some degree of success. The combination of soft AI, such as neural networks, and hard AI methods, such as alpha-beta pruned minimax game tree searching, is attempted

Nearly Optimal Minimax Tree Search?

by Aske Plaat, Jonathan Schaeffer, Wim Pijls, Arie De Bruin , 1994
"... Knuth and Moore presented a theoretical lower bound on the number of leaves that any fixed-depth minimax tree-search algorithm traversing a uniform tree must explore, the so-called minimal tree. Since real-life minimax trees aren't uniform, the exact size of this tree isn't known for most ..."
Abstract - Cited by 11 (10 self) - Add to MetaCart
Knuth and Moore presented a theoretical lower bound on the number of leaves that any fixed-depth minimax tree-search algorithm traversing a uniform tree must explore, the so-called minimal tree. Since real-life minimax trees aren't uniform, the exact size of this tree isn't known for most

Efficiency of Parallel Minimax Algorithm for Game Tree Search

by Plamenka Borovska, Milena Lazarova - INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND TECHNOLOGIES- COMPSYSTECH’07 , 2007
"... The paper investigates the efficiency of parallel minimax algorithms for search in a game tree. The game used as a case study is a tic-tac-toe. The suggested parallel computational model exploits tree partitioning at width for each level of the game tree and is based on combination of the parallel a ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
The paper investigates the efficiency of parallel minimax algorithms for search in a game tree. The game used as a case study is a tic-tac-toe. The suggested parallel computational model exploits tree partitioning at width for each level of the game tree and is based on combination of the parallel

APHID Game-Tree Search

by Mark G. Brockington, Jonathan Schaeffer - Journal of Parallel and Distributed Computing , 1997
"... This paper introduces the APHID (Asynchronous Parallel Hierarchical Iterative Deepening) gametree search algorithm. An APHID search is controlled by a master and a series of slave processors. The master searches the first d 0 ply of the game-tree repeatedly. The slaves are responsible for the bott ..."
Abstract - Cited by 41 (8 self) - Add to MetaCart
This paper introduces the APHID (Asynchronous Parallel Hierarchical Iterative Deepening) gametree search algorithm. An APHID search is controlled by a master and a series of slave processors. The master searches the first d 0 ply of the game-tree repeatedly. The slaves are responsible

Bias and pathology in minimax search

by A. Sadikov, I. Bratko, I. Kononenko - Theoretical Computer Science , 2005
"... This article presents the results of experiments designed to gain insight into the effect of the minimax algorithm on the error of a heuristic evaluation function. Two types of effect of minimax are considered: (a) evaluation accuracy (are the minimax backed-up values more accurate than the heuristi ..."
Abstract - Cited by 5 (1 self) - Add to MetaCart
the heuristic values themselves?), and (b) decision accuracy (are moves played by deeper minimax search better than those by shallower search?). The experiments were performed in the KRK chess endgame and in randomly generated game trees. The results show that, counter-intuitively, evaluation accuracy may

Searching Informed Game Trees

by Wim Pijls, Arie de Bruin , 1992
"... 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 ..."
Abstract - Cited by 14 (10 self) - Add to MetaCart
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
Results 1 - 10 of 780