title: A decision network account of reasoning about other people's choices.
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-directed choice or that do not rely on probabilistic inference.
authors.affiliation: Department of Humanities and Social Sciences, Rose-Hulman Institute of Technology, United States.
authors.forename: Alan
authors.initials: A
authors.lastname: Jern
authors.affiliation: Department of Psychology, Carnegie Mellon University, United States.
authors.forename: Charles
authors.initials: C
authors.lastname: Kemp
mesh_terms: D001499:Bayes Theorem; D002755:Choice Behavior; D003657:Decision Making; D006801:Humans; D008390:Markov Chains; D008960:Models, Psychological; D012919:Social Behavior; D013850:Thinking
keywords: Choice; Decision networks; Mental state reasoning; Social reasoning; Theory of mind