Computing approximate diagnoses by using approximate entailment

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Abstract

The most widely accepted models of diagnostic reasoning are all phrased in terms of the logical consequence relations. In work in recent years, Schaerf and Cadoli have proposed efficient approximations of the classical consequence relation. The central idea of this paper is to parameterise the notion of diagnosis over different approximations of the consequence relation. This yields a number of different approximations of classical notions of diagnosis. We derive results about the relation between approximate and classical notions of diagnosis. Our results are attractive for a number of reasons. We obtain more flexible notions of diagnosis, which can be adjusted to particular situations. Furthermore, we obtain efficient anytime algorithms for computing both approximate and classical diagnoses.
Original languageEnglish
Title of host publicationProceedings of the Fifth International Conference on Principles of Knowledge Representation and Reasoning ({KR'96})
Pages265-256
Publication statusPublished - 1996

Bibliographical note

A. ten Teije and Harmelen, F.A.H. van. Computing approximate diagnoses by using approximate entailment. In Proceedings of the Fifth International Conference on Principles of Knowledge Representation and Reasoning ({KR'96}). Pages 265-256. November 1996.

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