Encoding of Production Rules in a Connectionist Network

Abstract

The task of implementing a simple rule-based production system in a connectionist architecture is discussed. To implement a connectionist-based production system, it is essential to be capable of representing explicit rules by means of simple neuronlike computing units. The architecture described here uses a local representation based upon the instance oriented symbolic/connectionist expert system SC net. The problems of variable binding and variable value instantiation are solved in the context of this system. The network is built such that only one value is bound to a variable during each rule firing cycle. Issues regarding serialization and working memory consistency are also solved. An example implementation, the Farmer's Dilemma planning problem, is given to illustrate the potential of this approach. The article shows how many different rule bases may be mapped onto a connectionist architecture for parallel execution.