UC Merced Proceedings of the Annual Meeting of the Cognitive Science Society Title Babies, Variables, and Relational Correlations Publication Date Babies, Variables, and Relational Correlations

Michael Gasser, Eliana Colunga
Recent studies have shown that infants have access to highly useful language acquisition skills. On the one hand, they can segment a stream of unmarked syllables into words, based only on the statistical regularities present in it. On the other, they can abstract beyond these input-specific regularities and generalize to rules. It has been argued that these are two separate learning mechanisms, that the former is simply associationist whereas the latter requires variables. In this paper we
more » ... this paper we present a correlational approach to the learning of sequential regularities , and its implementation in a connectionist model, which accommodates both types of learning. We show that when a network is made out of the right stuff, specifically, when it has the ability to represent sameness and the ability to represent relations, a simple correlational learning mechanism suffices to perform both of these tasks. Crucially the model makes different predictions than the variable-based account.