{"pk":31684,"title":"Integrating Learning into Models of Human Memory: The Hebbian Recurrent Network","subtitle":null,"abstract":"We develop an interactive model of human mem-\nory called the Hebbian Recurrent Network ( HRN )\nwhich integrates work in the mathematical modeling\nof memory with that in error correcting connection-\nist networks. It incorporates the Matrix Model (Pike,\n1984) into the Simple Recurrent Network (SRN, El-\nman, 1989). The result is an architecture which has\nthe desirable memory characteristics of the matrix\nmodel such as low interference and massive general-\nization, but which is able to learn appropriate en-\ncodings for items, decision criteria and the control\nfunctions of memory which have traditionally been\nchosen a priori in the mathematical memory litera-\nture. Simulations demonstrate that the HRN is well\nsuited to a recognition task inspired by typical mem-\nory peiradigms. In comparison to the SRN , the HRN\nis able to learn longer lists, and is not degraded sig-\nnificantly by increasing the vocabulary size.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Submitted Presentations","is_remote":true,"remote_url":"https://escholarship.org/uc/item/0k24d99r","frozenauthors":[{"first_name":"Simon","middle_name":"","last_name":"Dennis","name_suffix":"","institution":"The University of Queensland","department":""},{"first_name":"Janet","middle_name":"","last_name":"Wiles","name_suffix":"","institution":"The University of Queensland","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"1993-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/31684/galley/22752/download/"}]}