A unified theory of heuristic evaluation functions and its application to learning
Jens Christensen, Richard E. Korf · 1986
WC prcscnt a characterization of heuristic evaluation functions Hhich unities their trcatmcnt in single-agent problems and two-person games. ‘l‘hc central result is that a useful heuristic function is one which dctcrmincs the outcome of a search and is invariant along a solution path. ‘I‘his local chnractcrization of heuristics can hc used to predict the cffcctivcncss of given heuristics and to automatically learn useful heuristic functions for problems. In one cxpcrimcnt, a set of rclntivc weights for the different chess pieces was automatically learned. A challenge for any theory of heuristic evaluation fimctions is to explain these anomalies. An additional challcngc is to present a consistent intcrprctation of heuristic functions in single-agent problems and two-player games. Surprisingly, the trcatmcnt in the litcraturc of heuristic starch in thcsc two diffcrcnt domains has