Combining heuristic reasoning with causal reasoning in diagnostic problem solving

In this paper we discuss two different approaches for the combination of heuristic and causal reasoning in diagnostic problem solving. In particular, we first present the two-level architecture CHECK which exploits both experiential knowledge and a deeper form of knowledge. While the former is represented by means of a frame-based formalism, the latter is based on a causal network representation. The co-operation of reasoning at the two levels is discussed: the results of the heuristic level are used to focus reasoning at the causal level. Diagnostic problem solving at the causal level has been logically characterized as a form of abductive reasoning. Because of some difficulties of the CHECK approach (mainly regarding the possible lack of consistency of two independently acquired knowledge bases) we investigated an alternative approach, represented by the AID architecture, which mainly relies on a causal representation of knowledge. In AID the abductive formalization of diagnosis plays a major role, and the reasoning process is focused by operational knowledge that is automatically synthesized from the causal model.