A general characterization of model-based diagnosis

Research output: Chapter in Book/Report/Conference proceedingsChapterpeer-review

Abstract

The Model-Based Diagnosis (MBD) framework developed by Reiter has been a strong theoretical foundation for MBD, yet is limited to models that are described in terms of logical sentences. We propose a more general framework that covers a wide range of modelling languages, ranging from AI-based languages (e.g., logic and Bayesian networks) to FDI-based languages (e.g., linear Gaussian models). We show that a graph-theoretic basis for decomposable system models can be augmented with several languages and corresponding inference algorithms based on valuation algebras.

Original languageEnglish
Title of host publicationFrontiers in Artificial Intelligence and Applications
EditorsGal A. Kaminka, Maria Fox, Paolo Bouquet, Eyke Hullermeier, Virginia Dignum, Frank Dignum, Frank van Harmelen
PublisherIOS Press BV
Pages1565-1566
Number of pages2
ISBN (Electronic)9781614996712
DOIs
Publication statusPublished - 2016
Event22nd European Conference on Artificial Intelligence, ECAI 2016 - The Hague, Netherlands
Duration: 29 Aug 20162 Sep 2016

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume285
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

Conference

Conference22nd European Conference on Artificial Intelligence, ECAI 2016
Country/TerritoryNetherlands
CityThe Hague
Period29/08/162/09/16

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