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Issue title: Intelligent Engineering Techniques for Knowledge Bases
Article type: Research Article
Authors: Wotawa, Franz; | Pill, Ingo; ;
Affiliations: Institute for Software Technology, Graz University of Technology, Graz, Austria. E-mails: {wotawa, ipill}@ist.tugraz.at
Note: [] The authors are listed in reverse alphabetical order.
Note: [] Corresponding author: Ingo Pill, Institute for Software Technology, Graz University of Technology, Inffeldgasse 16b/II, 8010 Graz, Austria. E-mail: [email protected]
Abstract: With model-based diagnosis, diagnoses for occurring faults can be directly computed from a given system model and actual observations about system behavior. Model-based diagnosis has been successfully accommodated to several purposes, including the diagnosis of space probes and configuration knowledge bases. Recent research includes extensions for distributed systems, motivated by the ever-growing system complexity and inherently distributed domains like service-oriented architectures. Previous work in this context lacks however a detailed analysis and classification approach that considers essential underlying issues like diagnosis architecture, utilized models, and abstract requirements that might stem from the application domain. In this paper, we will show an analysis of distributed system diagnosis and a characterization in the three dimensions mentioned.
Keywords: Model-based diagnosis, distributed diagnosis
DOI: 10.3233/AIC-2012-0548
Journal: AI Communications, vol. 26, no. 1, pp. 133-143, 2013
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