{"pk":30418,"title":"Learning Salience Anmong Featured Through Contingency in the CEL Framework","subtitle":null,"abstract":"Determining which features in an environment are salient given a task, salience assignment, is a central problem in machine learning. A related phenomenon, contingency ( the conditions under which relative salience among environemental features is acquired), is central to learning and memory in animal psychology. This paper presents an analysis of a set of empirical data on contingency and an algorithm for the salience assignment problem. The algorithm presented is implmented in a working computer profram which interacts with a simulated environement to produce contingent asssociative learning corresponding to relevant behavioral data. The model also makes specific empirical predictions that can be experimentally tested.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Paper Session 2","is_remote":true,"remote_url":"https://escholarship.org/uc/item/3nf6668t","frozenauthors":[{"first_name":"Richard","middle_name":"H.","last_name":"Granger","name_suffix":"","institution":"University of California, Irvine","department":""},{"first_name":"Jeffrey","middle_name":"C.","last_name":"Schlimmer","name_suffix":"","institution":"University of California, Irvine","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"1985-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/30418/galley/20267/download/"}]}