SINGULAR EXTENSIONS - ADDING SELECTIVITY TO BRUTE-FORCE SEARCHING

被引:46
作者
ANANTHARAMAN, T
CAMPBELL, MS
HSU, FH
机构
[1] Department of Computer Science, Carnegie-Mellon University, Pittsburgh
关键词
D O I
10.1016/0004-3702(90)90073-9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Brute-force alpha-beta search of games trees has proven relatively effective in numerous domains. In order to further improve performance, many brute-force game-playing programs have used the technique of selective deepening, searching more deeply on lines of play identified as important. Typically these extensions are based on static, domain-dependent knowledge. This paper describes a modification of brute-force search, singular extensions, that allows extensions to be identified in a dynamic, domain-independent, low-overhead manner. Singular extensions, when implemented in a chess-playing program, resulted in significant performance improvements. © 1990.
引用
收藏
页码:99 / 109
页数:11
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