A Symbolic-Connectionist Model of Relation Discovery
نویسندگان
چکیده
Relational reasoning is central in human cognition. Numerous computational models address the component processes of relational reasoning, however these models require the modeler to hand-code the vocabulary of relations on which the model operates. The acquisition of relational concepts remains poorly understood. We present a theory of relation discovery instantiated in a symbolic-connectionist model, which learns structured representations of attributes and relations from unstructured distributed representations of objects by a process of comparison, and subsequently refines these representations through a process of mapping-based schema induction.
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