Methodological Simplicity in Expert System Construction: The Case of Judgments and Reasoned Assumptions
Jon Doyle · 1983
Abstract: Probabilistic rules and their variants have recently supported several successful applications of expert systems, in spite of the difficulty of committing informants to particular conditional probabilities or “certainty factors, ” and in spite of the experimentally observed insensitivity of system performance to perturbations of the chosen values. Here we survey recent developments concerning reasoned assumptions which offer hope for avoiding the practical elusiveness of probabilistic rules while retaining theoretical power, for basing systems on the information unhesitatingly gained from expert informants, and recon-structing the entailed degrees of belief later. I owe much to Gerald Sussman, Johan de Kleer, Guy Steele, Drew McDermott and Marvin Minsky for inspiration on these topics. I also thank Joseph Schatz, Peter Szolovits, Randall