Young children integrate current observations, priors and agent information to predict others' actions.

ABSTRACT: From early on in life, children are able to use information from their environment to form predictions about events. For instance, they can use statistical information about a population to predict the sample drawn from that population and infer an agent's preferences from systematic violations of random sampling. We investigated whether and how young children infer an agent's sampling biases. Moreover, we examined whether pupil data of toddlers follow the predictions of a computational model based on the causal Bayesian network formalization of predictive processing. We formalized three hypotheses about how different explanatory variables (i.e., prior probabilities, current observations, and agent characteristics) are used to predict others' actions. We measured pupillary responses as a b

SUBMITTER: Kayhan E 

PROVIDER: S-EPMC6530825 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature