For most high-performance two-player game programs, a significant amount of time is devoted to developing the evaluation function. An important issue in this regard is how to take advantage of a large memory. For some two-player games, endgame databases have been an effective way of reducing search effort and introducing accurate values into the search. For some one-player games (puzzles), pattern databases have been effective at improving the quality of the heuristic values used in a search.
This paper presents a new approach to using endgame and pattern databases to assist in constructing an evaluation function for two-player games. Via abstraction, single-agent pattern databases are applied to two-player games. Positions in endgame databases are viewed as an abstraction of more complicated positions; database lookups are used as evaluation function features. These ideas are illustrated using Chinese checkers and chess. For each domain, even small databases can be used to produce strong game play. This research has relevance to the recent interest in building general game-playing programs. For two-player applications where pattern and/or endgame databases can be built, abstraction can be used to automatically construct an evaluation function.
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