An Approach to Verifying Completeness and Consistency in a Rule-Based Expert System

Suwa, Motoi, Scott, A. Carlisle, Shortliffe, Edward H.

AI Magazine 

We describe a program for verifying that a set of rules in an expert system comprehensively spans the knowledge of a specialized domain. The program has been devised and tested within the context of the ONCOCIN System, a rule-based consultant for clinical oncology. The stylized format of ONCOIN's rule has allowed the automatic detection of a number of common errors as the knowledge base has been developed. This capability suggests a general mechanism for correcting many problems with knowledge base completeness and consistency before they can cause performance errors.

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