This paper describes D^DALUS, a system that uses a variant of means-ends analysis to generate plans and uses an incremental learning algorithm to acquire probabilistic search heuristics from problem solutions. W e summarize DjEDALUS' approach to search, knowledge, organization, and learning, and examine its behavior on multi-column subtraction. W e then evaluate the system in terms of its consistency with known results on human problem solving, comparing it to other psychological models of learntng and planning.
