Decisions to intervene on causal systems are adaptively selected

Anna Coenen, Bob Rehder, Todd Gureckis

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

Abstract

How do people choose interventions to learn about a causal system? Here, we tested two possibilities: an optimal information sampling strategy which aims to discriminate between multiple hypotheses, and a second strategy that aims to confirm individual hypotheses. We show in Experiment 1 that individual behavior is best fit using a mixture of these two options. In a second experiment, we find that people are able to adaptively alter the strategies they use in response to their expected payoff in a particular task environment.

Original languageEnglish (US)
Title of host publicationProceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014
PublisherThe Cognitive Science Society
Pages343-348
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

Keywords

  • causal learning
  • information sampling
  • interventions

ASJC Scopus subject areas

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

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