Using chess knowledge to reduce search

Abstract

The current generation of computer chess programs select a move by exploring huge lookahead trees (millions of positions). Human masters, on the other hand, appear to use a knowledge-intensive approach to chess (see Chapter 2). They seem to have a huge number of stored “patterns,” and analyzing a position involves matching these patterns to suggest plans for attack or defense. This analysis is verified and possibly corrected by a small search of the game tree (tens of positions). Since the best humans still play better chess than the best programs, it is reasonable to explore computer programming strategies for using chess knowledge rather than extensive searching. This chapter describes a program named PARADISE (PAttern Recognition Applied to DIrecting SEarch) which uses this approach in an attempt to find the best move in tactically sharp middle game positions from the games of chess masters.