A theory of the discovery and predication of relational concepts. 论文

摘要

Relational thinking plays a central role in human cognition. However, it is not known how children and adults acquire relational concepts and come to represent them in a form that is useful for the purposes of relational thinking (i.e., as structures that can be dynamically bound to arguments). The authors present 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 (i.e., predicate them). The theory is instantiated as a computer program called DORA (Discovery Of Relations by Analogy). DORA is used to simulate the discovery of novel properties and relations, as well as a body of empirical phenomena from the domain of relational learning and the development of relational representations in children and adults.