Rule learning by seven-month-old infants

A fundamental task of language acquisition is to extract abstract algebraic rules. Three experiments show that 7-month-old infants attend longer to se ntences with unfamiliar structures than to sentences with familiar structur es. The design of the artificial language task used in these experiments en sured that this discrimination could not be performed by counting, by a sys tem that is sensitive only to transitional probabilities, or by a popular c lass of simple neural network models. Instead, these results suggest that i nfants can represent, extract, and generalize abstract algebraic rules.