A Bayesian framework for the development of belief-desire reasoning: Estimating inhibitory power

Abstract

A robust empirical finding in theory-of-mind (ToM) reasoning, as measured by standard false-belief tasks, is that children four years old or older succeed whereas three-year-olds typically fail in predicting a person's behavior based on an attributed false belief. Nevertheless, when the child's own belief is undermined by increasing their subjective uncertainty about the truth, as introduced in low-demand false-belief tasks, three-year-olds can better appreciate another person's false belief. Inhibition is believed to play a critical role in such developmental patterns. Within a Bayesian framework, using meta-data, we present the first computational implementation of inhibition, as specified by the Theory of Mind Mechanism (ToMM) model, to account for both the developmental shift from three to four years of age and the change in children's performances between high-demand and low-demand false-belief tasks. A Bayesian framework enables us to evaluate the predictive power of the model and infer the underlying psychological parameters. Together with behavioral evidence, we discuss the critical role of inhibitory control, as specified by ToMM, in children's theory-of-mind development.