Many organisms can predict future events from the statistics of past experience, but humans
also excel at making predictions by pure reasoning: integrating multiple sources of information,
guided by abstract knowledge, to form rational expectations about novel situations, never
directly experienced. Here, we show that this reasoning is surprisingly rich, powerful, and
coherent even in preverbal infants. When 12-month-old infants view complex displays of
multiple moving objects, they form time-varying expectations about future events that are a
systematic and rational function of several stimulus variables. Infants’ looking times are
consistent with a Bayesian ideal observer embodying abstract principles of object motion.
The model explains infants’ statistical expectations and classic qualitative findings about object
cognition in younger babies, not originally viewed as probabilistic inferences.
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