Publication: Exploiting Structural abstractions for ...

Master data
Title: Exploiting Structural abstractions for consistency based diagnosis of large configurator knowledge bases
Subtitle:
Abstract: Debugging, validation, and maintenance of configurator knowledge bases are important tasks for the success-ful deployment of product configuration systems, due to frequent changes (e.g., new component types, new regulations) in the configurable products. Model based diagnosis techniques have shown to be a promising approach to support the test engineer in identifying faulty parts in declarative knowledge bases. Given positive (existing configurations) and negative test cases, explanations for the unexpected behavior of the configuration systems can be calculated using a consistency based approach. For the case of large and complex knowledge bases, we show how the usage of hierarchical abstractions can reduce the computation times for the explanations and in addition gives the possibility to iteratively and interactively refine diagnoses from abstract to more detailed levels. Starting from a logical definition of configuration and diagnosis of knowledge bases, we show how a basic diagnostic algorithm can be extended to support hierarchical abstractions in the configuration domain. Finally, experimental results from a prototypical implementation using an industrial constraint based configurator library are presented
Keywords:
Publication type: Article in compilation (Authorship)
Publication date: 2000 (Print)
Published by: 14h European Conference on Artificial Intelligence (ECAI'2000) - configuration workshop
14h European Conference on Artificial Intelligence (ECAI'2000) - configuration workshop
to publication
 ( M. Stumptner )
Title of the series: -
Volume number: -
First publication: Yes
Page: pp. 23 - 28

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Publication date: 2000
ISBN: -
ISSN: -
Homepage: -

Assignment
Organisation Address
Fakultät für Technische Wissenschaften
  Institut für Artificial Intelligence und Cybersecurity
Universitätsstr. 65-67
A-9020 Klagenfurt
Austria
  -993705
   aics-office@aau.at
https://www.aau.at/en/aics/
To organisation
Universitätsstr. 65-67
AT - A-9020  Klagenfurt

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Peer reviewed
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  • Science to Science (Quality indicator: n.a.)
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