Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Connectionist inference models
Neural Networks
A connectionist model for predicate logic reasoning using coarse-coded distributed representations
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
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In this paper, we describe a model for reasoning using forward chaining for predicate logic rules and facts with coarse-coded distributed representations for instantiated predicates in a connectionist frame work. Distributed representations are known to give advantages of good generalization, error correction and graceful degradation of performance under noise conditions. The system supports usage of complex rules which involve multiple conjunctions and disjunctions. The system supports parallel and independent execution of predicate logic rule chains in a connectionist environment. The system solves the variable binding problem in a new way using coarse-coded distributed representations of instantiated predicates. Its performance with regard to generalization on unseen inputs and its ability to exhibit fault tolerance under noise conditions is studied and has been found to give good results.