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

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 ONCOCIN's I ules 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 pel fol mancc errors THI? BUILDERS FAKNOWI,EDGE-BASED cxpertsystern must ensure t,hat, t.he system will give its users accurate advice or correct solutions to t,heir problems. The process of verifying that a system is accurate and reliable has two distinct components: checking t,hat the knowledge base contains all necessary information and verifying that the program can interpret, and apply this information correctly. This process involves testing and refining the system's knowledge in order t,o discover and correct a variet.y of errors that, can arise during the process of transferring expertise from a human expert, to a computer syst,em. In this paper, we discuss some common problems in knowledge acquisition and debugging, and describe an aut,omxt,ed assistant for checking t,he completeness and consistency of the knowledge base in the ONCOCIN system (ShortJiffc, 1981).