Proceedings of the Annual Meeting of the Cognitive Science Society

Although the connectionist approach has lead to elegant solutions to a number of problems in cognitive science and artificial intelligence, its suitability for dealing with iHX)blems in knowledge representation and inference has often been questioned. This paper partially answers this criticism by demonstrating that effective solutions to certain problems in knowledge representation and limited inference can be found by adopting a connectionist approach.The paper iM-esents a connectionist realization of semantic networks, i.e. it describes h o w knowledge about concepts, their properties, and the hierarchical relationship between them may be encoded as an interpreter-free massively parallel network of simple processing elements that can solve an interesting class of inheritance and recognition problems extremely fast - in time proprotional to the depth of the conceptual hierarchy. The connectionist realization is based on an evidential formulation that leads to principled solutions to the problems of exceptions, multiple inheritance, and conflicting information during inheritance, and the best match or partial match computation during recognition.