Singular extensions: Adding selectivity to brute-force searching

Abstract

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.