Support Logic Programming
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Abstract
This paper describes a support logic programming system which uses a theory of support pairs to model various forms of uncertainty. It should find application to designing expert systems and is of a query language type like Prolog. Uncertainty associated with facts and rules is represented by a pair of supports and uses ideas from Zadeh's fuzzy set theory and Shafer's evidence theory. A calculus is derived for such a system and various models of interpretation given. The paper provides a form of knowledge representation and inference under uncertainty suitable for expert systems and a closed world assumption is not assumed. Facts not in the knowledge base are uncertain rather than assumed to be false.
