Explaining Choice Behavior: The Intentional Selection Assumption

Kelley Durkin, Leyla R. Caglar, Elizabeth Bonawitz, Patrick Shafto

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

2 Scopus citations

Abstract

How do people decide between several options presented to them? Normative accounts suggest the utilities of options are fixed, but subjective accounts suggest utilities depend on context. In the current paper, we propose a novel model of choice that may help reconcile these accounts. We propose that choice behavior may depend on an “Intentional Selection Assumption”: when people are presented with multiple options, they assume the options were intentionally selected by a person with specific questions in mind. Inferences about the intentional selection of options inform the chooser about the features that are intended to be most relevant. In this way, context can affect the desirability of a particular option, without requiring shifting utilities over features. Two behavioral experiments support the claim that participants are sensitive to intentional selection. We discuss the importance of taking choosers' assumptions about intentional selection into account in future investigations of choice behavior.

Original languageEnglish (US)
Title of host publicationProceedings of the 37th Annual Meeting of the Cognitive Science Society, CogSci 2015
EditorsDavid C. Noelle, Rick Dale, Anne Warlaumont, Jeff Yoshimi, Teenie Matlock, Carolyn D. Jennings, Paul P. Maglio
PublisherThe Cognitive Science Society
Pages614-619
Number of pages6
ISBN (Electronic)9780991196722
StatePublished - 2015
Event37th Annual Meeting of the Cognitive Science Society: Mind, Technology, and Society, CogSci 2015 - Pasadena, United States
Duration: Jul 23 2015Jul 25 2015

Publication series

NameProceedings of the 37th Annual Meeting of the Cognitive Science Society, CogSci 2015

Conference

Conference37th Annual Meeting of the Cognitive Science Society: Mind, Technology, and Society, CogSci 2015
Country/TerritoryUnited States
CityPasadena
Period7/23/157/25/15

All Science Journal Classification (ASJC) codes

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

Keywords

  • choice
  • computational modeling
  • intentional selection

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