Abstract
Preventive diagnosis is aimed at foreseeing likely future faults in a physical system before they actually occur. Although this task is extremely important in several practical application domains, there is currently no general theory of preventive diagnosis. This paper is an attempt to set up a foundation of such a theory. First, a definition of preventive diagnosis is proposed, and an abstract model that contains the main assumptions underlying this concept is developed. Later, a logical model of the preventive diagnosis task which outlines a problem-solving process, called Check-up And Foresee, is described. Attention is then focused on the appropriateness of the knowledge-based technology as a way for implementing the Check-up And Foresee approach. Finally, a high-level analysis of the fundamental knowledge sources involved in the task of preventive diagnosis is performed.
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L. Chittaro, G. Guida, C. Tasso and E. Toppano, Functional and teleological knowledge in the multi-modeling approach for reasoning about physical systems: a case study in diagnosis, IEEE Transactions on Systems, Man and Cybernetics, Vol. 23, No. 6, 1993, 1718–1751
R. Reiter, A theory of diagnosis from first principles, Artificial Intelligence, 32, 1987, 57–95
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© 1995 Springer-Verlag Berlin Heidelberg
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Guida, G., Zanella, M. (1995). Preventive diagnosis: Definition and logical model. In: Gori, M., Soda, G. (eds) Topics in Artificial Intelligence. AI*IA 1995. Lecture Notes in Computer Science, vol 992. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60437-5_34
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DOI: https://doi.org/10.1007/3-540-60437-5_34
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