Introduction:
Two experiments presented infants with artificial languages in which at least two generalizations were logically possible. The results demonstrate that infants made one of the two generalizations tested, the one which was most statistically consistent with the particular subset of the data they received.
I will focus on the induction problem - the situation in which a subset of input clearly has at least two formal descriptions. What does an infant learner exposed to such input do? There are at least three possibilities: One is that the infant discerns both patterns embodied in the input and can generalize based on either one. A second possibility is that being faced with evidence of two possible generalizations prevents the learner from generalizing at all. Finally, and perhaps most interestingly, the infant might show evidence of having discerned different formal descriptions for different subsets of the input, depending on which description better accounts for that particular input.
Infants in the diagonal condition were familiarized with a subset of the stimuli in which the only common feature was an abstract AAB or ABA pattern. Like the infants studied by Marcus et al. (1999), infants in this condition were able to generalize to new test stimuli, suggesting that they had made the intended generalization, having only been exposed to four stimulus types. Infants in the column condition, who were exposed to a different subset of the same larger data set, failed to make the generalization. This pattern of results is consistent with two possible interpretations: Infants exposed to input consistent with two different formal systems make no generalization at all. Or, infants generalize based on the formal description that is more likely to have generated the input.