Abstract
This is the first of two articles presenting an approach to rule-based expert systems for diagnostic tasks exploiting a purely neural architecture. Here, we outline the methodological options motivating this approach, and describe a forward and backward chaining mechanism on a system of production rules. This inference engine is furnished with an informative justification module, which exploits the fact that most individual neurons get a precise semantic assignment in terms of the literals appearing in production rules. the control and synchronization functions needed to schedule these processes are carried out by a neural network, too. © 1995 John Wiley & Sons, Inc.
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