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The Generation of Explanations within Evidential Reasoning Systems

One of the most highly touted virtues of knowledge-based expert systems is their ability to construct explanations of deduced lines of reasoning. However, there is a basic difficulty in generating explanations in expert systems that reason under uncertainty using numeric measures. In particular, systems based upon evidential reasoning using the theory of belief functions have lacked any facility for explaining their conclusions. In this paper we review the process whereby other expert system technologies produce explanations, and present a methodology for augmenting an evidential-reasoning system with a versatile explanation facility. The method, which is based on sensitivity analysis, has been implemented and a simple example of its use is described.