Probabilistic model-based diagnosis system

Jiah-Shing Chen; Sargur N. Srihari

doi:10.1117/12.56874

1 March 1992 Probabilistic model-based diagnosis system

Jiah-Shing Chen, Sargur N. Srihari

Proceedings Volume 1707, Applications of Artificial Intelligence X: Knowledge-Based Systems; (1992) https://doi.org/10.1117/12.56874
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

Diagnosis of a malfunctioning physical system is the task of identifying those component parts whose failures are responsible for discrepancies between observed and correct system behavior. The goal of interactive diagnosis is to repeatedly select the best information- gathering action to perform until the device is fixed. We developed a probabilistic diagnosis theory that incorporates probabilistic reasoning into model-based diagnosis. In addition to the structural and functional information normally used in model-based diagnosis, probabilities of component failure are also used to solve the two major subtasks of interactive model-based diagnosis: hypothesis generation and action selection. This paper describes a model-based diagnostic system built according to our probabilistic theory. The major contributions of this paper are the incorporation of probabilistic reasoning into model-based diagnosis and the integration of repair as part of diagnosis. The integration of diagnosis and repair makes it possible to effectively troubleshoot failures in complex systems.

Citation Download Citation

Jiah-Shing Chen and Sargur N. Srihari "Probabilistic model-based diagnosis system", Proc. SPIE 1707, Applications of Artificial Intelligence X: Knowledge-Based Systems, (1 March 1992); https://doi.org/10.1117/12.56874

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