{"pk":32891,"title":"Explanation-Based Retrieval in a Case-Based Learning Model","subtitle":null,"abstract":"Retrieving previous similar cases from a memory of cases is central to case-based reasoning systems. In most systems, this retrieval is done by a detailed indexing mechanism. Thagard and Holyoak argue that indexing is the wrong way to retrieve analogues. They propose a retrieval model (ARCS) based on a competing constraint satisfaction approach. In this paper, an explanation-based retrieval method (EBR) for retrieving analogues from a case-base with cases stored with respect to an interpretation of these cases as analyzed by a cognitive diagnostic component is described. The system is designed to the domain of problem solving in LISP. In a simulation study, it can be shown that the EBR-method performs equally well or even better than the ARCS-method.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Paper Presentations -- Reminding and Case Retrieval","is_remote":true,"remote_url":"https://escholarship.org/uc/item/1tb3q6xc","frozenauthors":[{"first_name":"Gerhard","middle_name":"","last_name":"Weber","name_suffix":"","institution":"University of Trier","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"1991-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/32891/galley/23951/download/"}]}