Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10334206 | Theoretical Computer Science | 2005 | 28 Pages |
Abstract
We argue that the mapping of an evaluation function from chess positions to heuristic values is of ordinal, but not interval scale. We identify a robust metric suitable for assessing the quality of an evaluation function, and present a novel method for computing this metric efficiently. Finally, we apply an empirical gradient-ascent procedure, also of our design, over this metric to optimize feature weights for the evaluation function of a computer-chess program. Our experiments demonstrate that evaluation function weights tuned in this manner give equivalent performance to hand-tuned weights.
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Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
D. Gomboc, M. Buro, T.A. Marsland,