Frugal preference formation

Nisheeth Srivastava, Paul R. Schrater

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

2 Scopus citations

Abstract

Most theories explaining how animals form preferences for their actions agree upon a basic outline: animals discover what is preferable through interactions with the world, store this information in memory, and recall it to help them decide what to do in a new situation. However, no single theory currently explains both how preferences are learned, and how they are recalled in a way that is compatible with empirical data. We advance precisely such a proposal in the form of a stochastic choice model where the decision agent learns what to do based on scale-free comparisons between options it observes in the world and at each decision instance recalls a subset of these comparison experiences in a manner that minimizes the metabolic costs of memory recall. In simulation, this model makes qualitatively accurate predictions connecting agent choices with various dynamic choice correlates documented in the literature on choice process models.

Original languageEnglish (US)
Title of host publicationProceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014
PublisherThe Cognitive Science Society
Pages1509-1514
Number of pages6
ISBN (Electronic)9780991196708
StatePublished - 2014
Event36th Annual Meeting of the Cognitive Science Society, CogSci 2014 - Quebec City, Canada
Duration: Jul 23 2014Jul 26 2014

Publication series

NameProceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014

Conference

Conference36th Annual Meeting of the Cognitive Science Society, CogSci 2014
Country/TerritoryCanada
CityQuebec City
Period7/23/147/26/14

Bibliographical note

Publisher Copyright:
© 2014 Proceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014. All rights reserved.

Keywords

  • artificial intelligence
  • Bayesian modeling
  • cognitive science
  • computer simulation
  • Decision-making
  • learning
  • mathematical modeling
  • memory

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