Semantic ambiguity resolution by parallel distributed, associative inference and contradiction detection

Proposes a PDAI&CD architecture aimed at constructing natural inference systems. The kernel consists of a mutually associative neural network which processes numerical patterns and of a logical system processing symbols. The associative part calls on context-dependent free-association of concepts based on the relations of concepts acquired from a dynamically changing outer world. In the logical part of the architecture, the results obtained by the neural network are checked, and emerging contradictions create feedback to the associative network and thus find a final optimum solution. WAVE, an implemented system, is introduced, and the authors show its application to the problem of ambiguity resolution in natural language understanding.