Abstract

The visual world of adults consists of objects at various distances, partly occluding one another, substantial and stable across space and time. The visual world of young infants, in contrast, is often fragmented and unstable, consisting not of coherent objects but rather surfaces that move in unpredictable ways. Evidence from computational modeling and from experiments with human infants highlights three kinds of learning that contribute to infants’ knowledge of the visual world: learning via association, learning via active assembly, and learning via visual-manual exploration. Infants acquire knowledge by observing objects move in and out of sight, forming associations of these different views. In addition, the infant’s own self-produced behavior—oculomotor patterns and manual experience, in particular—is an important means by which infants discover and construct their visual world