FOUNDATION AND APPLICATION OF KNOWLEDGE-BASE VERIFICATION

Anomalies such as redundant, contradictory, and deficient knowledge in a knowledge base are symptoms of probable errors. Detecting anomalies is a well-established method for verifying knowledge-based systems. A lthough many tools have been developed to perform anomaly detection, s everal important issues have been neglected, especially the theoretica l foundations and computational limitations of anomaly detection metho ds, and analyses of the utility of such tools in practical use. This a rticle addresses these issues by presenting a theoretical foundation o f anomaly detection methods, and by presenting empirical results obtai ned in applying one anomaly detection tool to perform verification on five real-world knowledge-based systems. The techniques presented appl y specifically to verifying rule-based knowledge bases without numeric al certainty measures. (C) 1994 John Wiley & Sons, Inc.