TitleModeling other minds: Bayesian inference explains human choices in group decision-making.
Publication TypeJournal Article
Year of Publication2019
AuthorsKhalvati K, Park SA, Mirbagheri S, Philippe R, Sestito M, Dreher J-C, Rao RPN
JournalSci Adv
Date or Month Published2019 11

To make decisions in a social context, humans have to predict the behavior of others, an ability that is thought to rely on having a model of other minds known as "theory of mind." Such a model becomes especially complex when the number of people one simultaneously interacts with is large and actions are anonymous. Here, we present results from a group decision-making task known as the volunteer's dilemma and demonstrate that a Bayesian model based on partially observable Markov decision processes outperforms existing models in quantitatively predicting human behavior and outcomes of group interactions. Our results suggest that in decision-making tasks involving large groups with anonymous members, humans use Bayesian inference to model the "mind of the group," making predictions of others' decisions while also simulating the effects of their own actions on the group's dynamics in the future.

Alternate JournalSci Adv
Citation Key15617
PubMed ID31807706
PubMed Central IDPMC6881156
Grant ListR01 MH112166 / MH / NIMH NIH HHS / United States