Computational Models of Memory Search

Posted: 16 Jan 2020

See all articles by Michael J. Kahana

Michael J. Kahana

University of Pennsylvania - Department of Psychology

Date Written: January 2020

Abstract

The capacity to search memory for events learned in a particular context stands as one of the most remarkable feats of the human brain. How is memory search accomplished? First, I review the central ideas investigated by theorists developing models of memory. Then, I review select benchmark findings concerning memory search and analyze two influential computational approaches to modeling memory search: dual-store theory and retrieved context theory. Finally, I discuss the key theoretical ideas that have emerged from these modeling studies and the open questions that need to be answered by future research.

Suggested Citation

Kahana, Michael J., Computational Models of Memory Search (January 2020). Annual Review of Psychology, Vol. 71, pp. 107-138, 2020, Available at SSRN: https://ssrn.com/abstract=3520444 or http://dx.doi.org/10.1146/annurev-psych-010418-103358

Michael J. Kahana (Contact Author)

University of Pennsylvania - Department of Psychology ( email )

3815 Walnut Street
Philadelphia, PA 19104-6196
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Abstract Views
258
PlumX Metrics