Evaluation function tuning via ordinal correlation

Abstract

Heuristic search effectiveness depends directly upon the quality of heuristic evaluations of states in the search space. We show why ordinal correlation is relevant to heuristic search, present a metric for assessing the quality of a static evaluation function, and apply it to learn feature weights for a computer chess program. © 2004 by Springer Science+Business Media New York.