Content area
Abstract
Relational thinking is ubiquitous in human cognition. However, little is known about how we discover relational concepts. It is difficult to account for how we learn relational concepts from examples because it is an underconstrained problem. The present paper proposes a theory of how a psychologically and neurally plausible cognitive architecture can discover relational concepts from examples and represent them as explicit structures (predicates) that can take arguments. Our theory is embodied in a computer simulation program called DORA (Discovery Of Relations by Analogy). DORA is used to simulate the discovery of novel properties and relations, and a body of empirical phenomena from the domain of relational learning and the development of relational representations in children and adults. The limitations of the present theory and directions for future research are discussed.
