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Consistency-based Diagnosis of Configuration Knowledge Bases

Alexander Felfernig, Gerhard E. Friedrich, Dietmar Jannach, Markus Stumptner

Configuration problems are a thriving application area for declarative knowledge representation that currently experiences a constant increase in size and complexity of knowledge bases. Automated support of the debugging of such knowledge bases is a necessary prerequisite for effective development of configurators. We show that this task can be achieved by consistency based diagnosis techniques. Based on the formal definition of consistency based configuration we develop a framework suitable for diagnosing configuration knowledge bases. During the test phase of configurators, valid and invalid examples are used to test the correctness of the system. In case such examples lead to unintended results, debugging of the knowledge base is initiated. The examples used for testing are combined to identify faulty chunks of knowledge. Starting from a clear definition of diagnosis in the configuration domain we develop an algorithm based on conflicts and exploit the properties of positive examples to reduce consistency checks. Our framework is general enough for its straightforward adaptation to diagnosing customer requirements. Given a validated knowledge base our approach can then be used to identify unachievable conditions during configuration sessions.

Keywords: Configuration, Diagnosis

Citation: Alexander Felfernig, Gerhard E. Friedrich, Dietmar Jannach, Markus Stumptner: Consistency-based Diagnosis of Configuration Knowledge Bases. In W.Horn (ed.): ECAI2000, Proceedings of the 14th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2000, pp.146-150.

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ECAI-2000 is organised by the European Coordinating Committee for Artificial Intelligence (ECCAI) and hosted by the Humboldt University on behalf of Gesellschaft für Informatik.