Journal article

A decision network account of reasoning about other people's choices

Alan Jern, Charles Kemp

COGNITION | ELSEVIER | Published : 2015

Abstract

The ability to predict and reason about other people's choices is fundamental to social interaction. We propose that people reason about other people's choices using mental models that are similar to decision networks. Decision networks are extensions of Bayesian networks that incorporate the idea that choices are made in order to achieve goals. In our first experiment, we explore how people predict the choices of others. Our remaining three experiments explore how people infer the goals and knowledge of others by observing the choices that they make. We show that decision networks account for our data better than alternative computational accounts that do not incorporate the notion of goal-..

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Grants

Awarded by National Science Foundation (NSF)


Awarded by NIMH Training Grant


Funding Acknowledgements

Data from Experiments 3 and 4 were presented at the 33rd Annual Conference of the Cognitive Science Society. We thank Jessica Lee for helping to collect the data for Experiments 1 and 2. We thank David Danks for feedback on the development of this work, and Jean-Francois Bonnefon, Mark Steyvers, and two anonymous reviewers for feedback on the manuscript. This work was supported by the Pittsburgh Life Sciences Greenhouse Opportunity Fund and by the National Science Foundation (NSF) Grant CDI-0835797. Alan Jern was supported in part by NIMH Training Grant T32MH019983.