The University of Edinburgh -
Division of Informatics
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Research Paper #732

Title:An Extension of the Temporal Synchrony Approach to Dynamic Variable Binding in a Connectionist Inference System
Authors:Park,N; Robertson,DS; gardner,K
Date:Jan 1995
Presented:Accepted for publication in the special issue on "Knowledge Based Neural Networks" planned by the Journal Knowledge-Based Systems
Abstract:The relationship between symbolism and connectionism has been one of the major issues in recent Artificial Intelligence research. An increasing number of researchers from each side have tried to adopt desirable characteristics of the other. A major open question in this field is the extent to which a connectionist architecture can accommodate basic concepts of symbolic inference, such as a dynamic variable binding mechanism and a rule and fact encoding mechanism involving n-ary predicates. One of the current leaders in this area is the connectionist rule-based system proposed by Shastri and Ajjanagadde. We demonstrate that the mechanism for variable binding which they advocate is fundamentally limited and show how a reinterpretation of the primitive components and corresponding modifications of their system can extend the range of inference which can be supported. Our extension hinges on the basic structural modification of the network components and further modification of the rule and fact encoding mechanism. These modifications allow the extended model to have more expressive power in dealing with symbolic knowledge such as unification of terms across many groups of unifying arguments.

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