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QUESCENCE
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Quiescence search is an algorithm typically used to evaluate minimax game trees in game-playing computer programs. It mitigates the effect of the horizon problem faced by AI engines for various games like chess and Go. * Human players usually have enough intuition to decide whether to abandon a bad-looking move, or search a promising move to a great depth. A quiescence search attempts to emulate this behavior by instructing a computer to search "interesting" positions to a greater depth than "quiet" ones to make sure there are no hidden traps and to get a better estimate of its value. * Any sensible criterion may be used to distinguish "quiet" moves from "noisy" moves; high activity (high movement on a chess board, extensive capturing in Go, for example) is commonly used for board games. As the main motive of quiescence search is usually to get a good value out of a poor evaluation function, it may also make sense to detect wide fluctuations in values returned by a simple heuristic evaluator over several ply. Modern chess engines may search certain moves up to 2 or 3 times deeper than the minimum. In highly "unstable" games like Go and reversi, a rather large proportion of computer time may be spent on quiescence searching. |
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