Lecture Notes in Computer Science vol:3180 pages:445-454
As their field of application has evolved and matured, the importance of verifying knowledge-based systems is now widely recognized. Nevertheless, some problems have remained. In this paper, we address the poor scalability to larger systems of the computation methods commonly applied to rule-chain anomaly checking. To tackle this problem, we introduce a novel anomaly checking method based on binary decision diagrams (BDDs), a technique emanating mainly from the hardware design community. In addition, we present empirical evidence of its computational efficiency, especially on rule bases with a deeper inference space.