Uncertain Inference in Knowledge‐Based Systems

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Abstract
The role of uncertainty analysis in the development of computer knowledge bases for civil engineering systems is discussed. It is argued that the term “expert system” should be replaced by “advice system” to avoid misunderstandings between the designers and users of such systems. An engineer is an expert to the extent that he is a responsible decision maker. The computer can only advise him; it cannot replace him. A new inference method of direct use in advice systems is presented. The method combines features of the theory of fuzzy sets, Shafer's theory of evidence and probability theory. The method follows the Horn clause logic representation of Prolog. Unlike probability theory, it does not rely upon a closed‐world form of knowledge representation, and can allow the modeling of total uncertainty. The Prolog form of negation by failure is not used. The method involves the use of necessary and possibility measures for the truth or dependability of a proposition. Examples are given of its use and a small model knowledge base for an advice system is described.

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