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Verification of Knowledge-Based Systems Using Predicate/Transition Nets

As expert-system technology gains broader acceptance, the need to build and maintain large-scale knowledge-based systems (KBSs) will assume greater importance. Traditional approaches to KBS verification generally contain no predicate/transition (PrT) net models, thus making them slow for the large-scale KBS with chained errors. This paper proposes an attractive alternative to KBS verification, in which the KBS is modeled as a PrT-net model. Then, the least fixpoint semantics of the PrT-net model can be introduced into the KBS for the purpose of speeding up the computations of the KBSs. The significance of this paper is that seven propositions are formulated to detect errors of redundancy, subsumption, unnecessary condition, circularity, inconsistency, dead end, and unreachable goal. Thus, the performance of a computer-aided-design tool for KBSs can be improved to some extent. Meanwhile, specification languages, including Programming in Logic, Frame-and-Rule-Oriented Requirements Specification Language, and the like, are suitable to this approach.