VERIFICATION OF QUALITATIVE PROPERTIES OF RULE-BASED EXPERT-SYSTEMS

Frequently expert systems are developed to operate in dynamic environm ents where they must reason about time-varying information and generat e hypotheses, conclusions, and process in puts that can drastically in fluence the environment within which they operate. For instance, exper t systems used for fault diagnosis and fault accommodation in nuclear power plants reason over sensor data and operator inputs, form fault h ypotheses, make recommendations pertaining to safe process operation, and in crisis situations could generate command inputs to the process to help maintain safe operation. Clearly, there is a pressing need to verify and certify, that such expert systems are dependable in their o peration and can reliably maintain adequate performance levels. In thi s article we develop a mathematical approach to verifying qualitative properties of rule-based expert systems that operate in dynamic and un certain environments. First, we provide mathematical models for the ex pert system (including the knowledge-base and inference engine) and fo r the mechanisms for interfacing to the user inputs and the dynamic pr ocess. Next, using these mathematical models, we show that while the s tructure and interconnection of information in the knowledge base infl uence the expert system's ability to react appropriately in a dynamic environment, the qualitative properties of the full knowledge-base/inf erence engine loop must be considered to fully characterize an expert system's dynamic behavior: To illustrate the verification approach, we show how to model and analyze the qualitative properties of rule-base d expert systems that solve a water-jug filling problem and a simple p rocess control problem. Finally, in our concluding remarks, we highlig ht some limitations of our approach and provide some future directions for research.