DEFT solutions to final testing

Abstract

A complete approach to reasoning under uncertainty requires support for both identification of the appropriate hypothesis space and ranking hypotheses based on available evidence. We present a hybrid reasoning scheme that combines symbolic and numerical methods for uncertainty management to provide efficient and effective support for both of these tasks. The hybrid is based on symbolic techniques adapted from assumption-based truth maintenance systems (ATMS), combined with numerical methods adapted from the Dempster/Shafer theory of evidence, as extended in Baldwin's Support Logic Programming system. The hybridization is achieved by viewing an ATMS as a symbolic algebra system for uncertainty calculations. This technique has several major advantages over conventional methods for performing inference with numerical certainty estimates in addition to the ability to dynamically determine hypothesis spaces, including improved management of dependent and partially independent evidence, faster run-time evaluation of propositional certainties, and the ability to query the certainty value of a proposition from multiple perspectives.