Predicting Short-Term Remembering as Boundedly Optimal Strategy Choice

Andrew Howes, Geoffrey B. Duggan, Kiran Kalidindi, Yuan Chi Tseng, Richard L. Lewis

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

It is known that, on average, people adapt their choice of memory strategy to the subjective utility of interaction. What is not known is whether an individual's choices are boundedly optimal. Two experiments are reported that test the hypothesis that an individual's decisions about the distribution of remembering between internal and external resources are boundedly optimal where optimality is defined relative to experience, cognitive constraints, and reward. The theory makes predictions that are tested against data, not fitted to it. The experiments use a no-choice/choice utility learning paradigm where the no-choice phase is used to elicit a profile of each participant's performance across the strategy space and the choice phase is used to test predicted choices within this space. They show that the majority of individuals select strategies that are boundedly optimal. Further, individual differences in what people choose to do are successfully predicted by the analysis. Two issues are discussed: (a) the performance of the minority of participants who did not find boundedly optimal adaptations, and (b) the possibility that individuals anticipate what, with practice, will become a bounded optimal strategy, rather than what is boundedly optimal during training.

Original languageEnglish
Pages (from-to)1192-1223
Number of pages32
JournalCognitive Science
Volume40
Issue number5
DOIs
Publication statusPublished - 2016 Jul 1

All Science Journal Classification (ASJC) codes

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Predicting Short-Term Remembering as Boundedly Optimal Strategy Choice'. Together they form a unique fingerprint.

Cite this