Abstract
Selecting the next measurement point in order to discriminate among candidate diagnoses is a crucial task for diagnosis system. We present a generic system which allows the fast and effective realization of different measurement selection strategies for model-based diagnosis systems. The minimum entropy technique used in the General Diagnostic Engine (Gde) and a simplification of it presented in [de Kleer 89] are two possible instances of this system. Several other techniques based on this framework are presented, including another simplification of the minimum entropy technique which overcomes deficiencies of [de Kleer 89].
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Johan de Kleer. An assumption-based tms. Artificial Intelligence, 28(2), 1986.
Johan de Kleer. Entropy without probablities. Technical Report SSL P89-00056, XEROX PARC, 1989.
Johan de Kleer and Brian C. Williams. Diagnosing multiple faults. Artificial Intelligence, 32(1), 1987.
Johan de Kleer and Brian C. Williams. Diagnosis with behavioral modes. In Proceedings 11th International Joint Conference on Artificial Intelligence, 1989.
Oskar Dressler. Diagnosis as Coherent Assumption Sets. Presented at the International Workshop on Principles of Diagnosis, 1990.
Peter Struss and Oskar Dressler. Physical negation — integrating fault models into the general diagnostic engine. In Proceedings 11th International Joint Conference on Artificial Intelligence, 1989.
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© 1990 Springer-Verlag Berlin Heidelberg
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Freitag, H. (1990). A generic measurement proposer. In: Gottlob, G., Nejdl, W. (eds) Expert Systems in Engineering Principles and Applications. ESE 1990. Lecture Notes in Computer Science, vol 462. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-53104-1_33
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DOI: https://doi.org/10.1007/3-540-53104-1_33
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Online ISBN: 978-3-540-46711-3
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