Author: Tord Romstad
Date: 06:57:45 08/24/04
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On August 24, 2004 at 06:14:32, Uri Blass wrote: >On August 24, 2004 at 04:57:02, Tord Romstad wrote: > >>Making the static eval aware of its limitations offers many interesting >>possibilities, and I think there are many valuable and important ideas >>waiting to be found by the adventurous programmer here. The basic >>idea is to extend in positions where the static eval is likely to be >>highly inaccurate, and to reduce in positions where it is likely to >>be very accurate (internal node recognizers is an extreme special case). > >The idea is simple but the problem is to write evaluation to evaluate the >variety of the score. In general, it is of course very difficult. But a few simple special cases can be implemented rather easily. One case was the one I described in my previous message: Winning material advantage for one side, a very strong attack for the other side. A similar case is when a huge material advantage is compensated by dangerous passed pawns. In both of these cases, the static eval is likely to be highly unreliable, and it makes sense to extend. For reductions, consider the case of a simple endgame where one side is ahead by a rook and the other side has no passed pawns, and the stronger side has no hanging pieces. In such situations, the winning score returned by the static eval is almost certainly correct, and reducing the depth is relatively safe. Perhaps it would be possible to improve and generalize such techniques by statistical methods. Start with a huge set of positions from real games, along with the results of all the games. Let your chess engine evaluate all the positions, and look at the values of all the components of the evaluation function (material, pawn structure, mobility, centre control, king safety, hanging/pinned pieces, etc.). By studying the data, it is possible that we could find formulas to make crude estimates of the probability distribution of the three possible results based on the "evaluation vector". Tord
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