Report Number: CS-TR-82-922
Institution: Stanford University, Department of Computer Science
Title: An approach to verifying completeness and consistency in a rule-based expert system
Author: Suwa, Motoi
Author: Scott, A. Carlisle
Author: Shortliffe, Edward H.
Date: June 1982
Abstract: 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 ONCOCIN's rules 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.