Deciding to Remember: Memory Maintenance as a Markov Decision Process

Jordan W. Suchow, Thomas L. Griffiths

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Working memory is a limited-capacity form of human memory that actively holds information in mind. Which memories ought to be maintained? We approach this question by showing an equivalence between active maintenance in working memory and a Markov decision process in which, at each moment, a cognitive control mechanism selects a memory as the target of maintenance. The challenge of remembering is then finding a maintenance policy well-suited to the task at hand. We compute the optimal policy under various conditions and define plausible cognitive mechanisms that can approximate these optimal policies. Framing the problem of maintenance in this way makes it possible to capture in a single model many of the essential behavioral phenomena of memory maintenance, including directed forgetting and self-directed remembering. Finally, we consider the case of imperfect metamemory - where the current state of memory is only partially observable - and show that the fidelity of metamemory determines the effectiveness of maintenance.

Original languageEnglish (US)
Title of host publicationProceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016
EditorsAnna Papafragou, Daniel Grodner, Daniel Mirman, John C. Trueswell
PublisherThe Cognitive Science Society
Pages2063-2068
Number of pages6
ISBN (Electronic)9780991196739
StatePublished - 2016
Externally publishedYes
Event38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016 - Philadelphia, United States
Duration: Aug 10 2016Aug 13 2016

Publication series

NameProceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016

Conference

Conference38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016
Country/TerritoryUnited States
CityPhiladelphia
Period8/10/168/13/16

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

Keywords

  • Markov Decision Process
  • cognitive control
  • memory maintenance
  • working memory

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