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Summary: NEURAL COMPUTING AND PRODUCTION SYSTEMS*
Michael A. Sartori and Panos J. Antsnklis
Department of Elecmcal and Computer Engineering
University of Notre Dame
Notre Dame, IN 46556
ABSTRACT
The application of neural computing to the problem of
matching in production systems is addressed. The computation time
required by this problem can be significantly reduced by using the
massive parallelism and pattern recognition capabilities available
through neural computing. A new neural computing model, called
here the ProNet, is introduced and explained in detail. The ProNet is
applied to the match phase of the production system interpreter in an
attempt to yield a reduction in time and space requirements by
matching a!: of the productions to all of the working memory elements
simultaneously.
1.0 INTRODUCTION
The production system, a special type of expert system, will
probably continue to be used to assist both humans and computers in
specific tasks for future applications of artificial intelligence to
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