Proceedings of the Annual Meeting of the Cognitive Science Society

This paper describes an efficient connectionist knowledge representation and reasoning system that combines rule-based reasoning with reasoning about inheritaince and classification within an IS-A hierarchy. In addition to a type hierarchy, the proposed system can encode generic facts such as 'Cats prey on birds' and rules such as 'if x preys on y then y is scared of x' and use them to infer that Tweety (who is a Canary) is scared of Sylvester (who is a cat). The system can also encode qualified rules such as 'if an animate agent walks into a solid object then the agent gets hurt'. The proposed system can answer queries in time that is only proportional to the length of the shortest derivation of the query and is independent of the size of the knowledge base. The system maintains and propagates variable bindings using temporally synchronous - i.e., in-phase - firing of appropriate nodes.