Proceedings of the Annual Meeting of the Cognitive Science Society

Humans and animals have the ability to learn complicated configurations of environmental cues that are predictive of important events. In cljissical conditioning, this task is called configural conditioning. Psychologists have studied this phenomenon since Pavlov's time, yet several of the contemporary learning models provide only partially satisfactory explanations. Most models provide mechanisms which select among possible predictive stimuli, but they fail to explicitly identify predictive combinations of stimuli and are thus restricted to learning only a relatively simple set of possible associations. In this paper we discuss a learning method which accounts for some configural conditioning results. Using an implemented system, we demonstrate the effectiveness of this method by modeling configural conditioning data from a pair of representative experimental studies.