A Distributed Connectionist Representation for Concept Structures
Technical rept. 15 Sep 1986-14 Sep 1991
CARNEGIE-MELLON UNIV PITTSBURGH PA ARTIFICIAL INTELLIGENCE AND PSYCHOLOGY PROJECT
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We describe a representation for frame-like concept structures in a neural network called DUCS. Slot names and slot fillers are diffuse patterns of activation spread over a collection of units. Our choice of a distributed representation gives rise to certain useful properties not shared by conventional frame systems. One of these is the ability to encode fine semantic distinctions as subtle variations on the canonical pattern for a slot. DUCS typically maintains several concepts simultaneously in its concept memory it can retrieve a concept given one or more slots as cues. We show how Hintons notion of a reduced description can be used to make one concept fill a slot in another. Keywords Artificial intelligence, Machine learning, Connectionsim, Short-term memory, Distributed representation, Frames.