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A rational approach to memory search termination
Affiliation:1. Department of Psychological Sciences, Birkbeck University of London, Malet Street, WC1E 7HX London, UK;2. Department of Psychology, University of Maryland at College Park, College Park, MD 20742, USA;1. Virginia Mason Medical Center, 1100 Ninth Avenue, Seattle, WA 98111, USA;2. Department of Urology, Stony Brook Medicine, 101 Nicolls Road, HSC Level 9-040, Stony Brook, NY 11794, USA;1. Department of Orthopaedic Surgery, Yamagata University Faculty of Medicine, Yamagata, Japan;2. Department of Orthopaedic Surgery, Yoshioka Hospital, Yamagata, Japan;3. Yamagata Prefectural University of Health Sciences, Yamagata, Japan;1. Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China;2. University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China;3. Institut für Astronomie und Astrophysik, Sand 1, 72076 Tübingen, Germany;4. Department of Physics, Tsinghua University, Beijing 100084, China;5. Department of Astronomy, Beijing Normal University, Beijing 100088, China;6. Department of Engineering Physics, Tsinghua University, Beijing 100084, China;7. Key Laboratory of Space Astronomy and Technology, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China;8. Sabancı University, Faculty of Engineering and Natural Science, İstanbul 34956, Turkey
Abstract:An important component of many, if not all, real-world retrieval tasks is the decision to terminate memory search. Despite its importance, systematic evaluations of the potential rules for terminating search are scarce. Recent work has focused on two variables: the total time spent in memory search before search is terminated and the exit latency (the time between the last retrieved item and the time of search termination). These variables have been shown to limit the number of plausible rules for terminating memory search. Here, we introduce an alternative stopping rule based on a rational moment-to-moment cost–benefit analysis and derive a closed-form expression of the exit latency function using this rational approach. We show the model’s ability to capture critical latency data and make testable predictions about the influence of changing the relative costs and benefits of memory search. Results from an experiment are presented that support the model’s predictions. We conclude that the decision to terminate memory search is based on moment-to-moment changes in subjective utility of retrieved memories.
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