Learning and making novel predictions about others' preferences

Natalia Vélez, Yuan Chang Leong, Chelsey Pan, Jamil Zaki, Hyowon Gweon

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

1 Scopus citations

Abstract

We often make decisions on behalf of others, such as picking out gifts or making restaurant recommendations. Yet, without direct access to others' preferences, our choices on behalf of others depend on what we think they like. Across two experiments, we examined whether and how accurately people are able to infer others' preferences by observing their choices. Our results suggest that people are capable of making reasonably accurate predictions about what others will choose next, given what they have chosen before. These results lay the groundwork to systematically study how people make novel predictions about others' preferences, and when different strategies might be appropriate.

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
Pages966-971
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

  • Theory of Mind
  • decision-making
  • preference learning
  • social cognition

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