Rational quantitative attribution of beliefs, desires, and percepts in human mentalizing

TitleRational quantitative attribution of beliefs, desires, and percepts in human mentalizing
Publication TypeJournal Article
Year of Publication2017
AuthorsBaker, CL, Jara-Ettinger, J, Saxe, R, Tenenbaum, JB
JournalNature Human Behavior
Date Published03/2017
KeywordsHuman behaviour, Social behaviour

Social cognition depends on our capacity for ‘mentalizing’, or explaining an agent’s behaviour in terms of their mental states. The development and neural substrates of mentalizing are well-studied, but its computational basis is only beginning to be probed. Here we present a model of core mentalizing computations: inferring jointly an actor’s beliefs, desires and percepts from how they move in the local spatial environment. Our Bayesian theory of mind (BToM) model is based on probabilistically inverting artificial-intelligence approaches to rational planning and state estimation, which extend classical expected-utility agent models to sequential actions in complex, partially observable domains. The model accurately captures the quantitative mental-state judgements of human participants in two experiments, each varying multiple stimulus dimensions across a large number of stimuli. Comparative model fits with both simpler ‘lesioned’ BToM models and a family of simpler non-mentalistic motion features reveal the value contributed by each component of our model.

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