Abstract
It is often possible to describe the correct functioning of a system by a mathematical model. As long as observations or measurements correspond to the predictions made by the model, the system may be assumed to be functioning correctly. When, however, a discrepancy arises between the observations and the model-based predictions, then an explanation for this fact has to be found. The foundation of this approach to diagnostics has been laid by Reiter (1987). The explanations generated by his method, called diagnoses, are not unique in general. In addition, they are not weighed by a likelihood measure which would make it possible to compare them. We propose here the theory of hints — an interpretation of the Dempster-Shafer Theory of Evidence — as a very natural and general method for model-based diagnostics (for an introduction to the theory of hints, see (Kohlas & Monney, 1995)). Note that (Peng & Reggia, 1990) and (DeKleer & Williams, 1987) also discuss probabilistic approaches to diagnostic problems.
Research supported by grants No. 21-30186.90 and 21-32660.91 of the Swiss National Foundation for Research, Esprit Basic Research Activity Project DRUMS II (Defeasible Reasoning and Uncertainty Management).
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References
DeKleer, J., & Williams, B.C. 1987. Diagnosing Multiple Faults. Artificial Intelligence, 32, 97–130.
Kohlas, J., & Monney, P.A. 1995. A Mathematical Theory of Hints. An Approach to the Dempster-Shafer Theory of Evidence. Lecture Notes in Economics and Mathematical Systems, vol. 425. Springer.
Peng, Y., & Reggia, J. 1990. Aductive Inference Model for Diagnostic Problem Solving. Springer.
Reiter, R. 1987. A Theory of Diagnosis From First Principles. Artificial Intelligence, Elsevier Science Publisher B. V. (Amsterdam), 32, 57–95.
Shenoy, P. 1994. Using Dempster-Shafer's Belief Function Theory in Expert Systems. Pages 395–414 of: Yager, R.R., Kacprzyk, J., & Fedrizzi, M. (eds), Advances The Dempster-Shafer Theory of Evidence. Wiley.
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Kohlas, J., Monney, P.A., Haenni, R., Lehmann, N. (1995). Model-based diagnostics using hints. In: Froidevaux, C., Kohlas, J. (eds) Symbolic and Quantitative Approaches to Reasoning and Uncertainty. ECSQARU 1995. Lecture Notes in Computer Science, vol 946. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60112-0_30
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DOI: https://doi.org/10.1007/3-540-60112-0_30
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