A general characterization of Model-Based Diagnosis

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Date
2016-01
Authors
Provan, Gregory
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IOS Press
Published Version
10.3233/978-1-61499-672-9-1565
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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.
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Keywords
MBD , AI , Logic , Bayesian , FDI
Citation
Provan, G. (2016) 'A general characterization of Model-Based Diagnosis' (from proceedings of the Twenty-second European Conference on Artificial Intelligence (ECAI 2016),The Hague, The Netherlands, 29th August - 2nd September), Frontiers in Artificial Intelligence and Applications, 285, pp. 1565-1566. doi:10.3233/978-1-61499-672-9-1565
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https://hdl.handle.net/10468/3770
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Insight Centre for Data Analytics - Conference Items
Computer Science - Conference Items
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© 2016, the Authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0)