Decision-Theoretic Troubleshooting: A Framework for Repair and Experiment

We develop and extend existing decision-theoretic methods for troubleshooting a nonfunctioning device. Traditionally, diagnosis with Bayesian networks has focused on belief updating--determining the probabilities of various faults given current observations. In this paper, we extend this paradigm to include taking actions. In particular, we consider three classes of actions: (1) we can make observations regarding the behavior of a device and infer likely faults as in traditional diagnosis, (2) we can repair a component and then observe the behavior of the device to infer likely faults, and (3) we can change the configuration of the device, observe its new behavior, and infer the likelihood of faults. Analysis of latter two classes of troubleshooting actions requires incorporating notions of persistence into the belief-network formalism used for probabilistic inference.

[1]  Ronald A. Howard,et al.  Value of Information Lotteries , 1967, IEEE Trans. Syst. Sci. Cybern..

[2]  Brian C. Williams,et al.  Diagnosing Multiple Faults , 1987, Artif. Intell..

[3]  D. Heckerman,et al.  Toward Normative Expert Systems: Part I The Pathfinder Project , 1992, Methods of Information in Medicine.

[4]  Ross D. Shachter,et al.  Decision-Theoretic Foundations for Causal Reasoning , 1995, J. Artif. Intell. Res..

[5]  David Heckerman,et al.  Causal independence for probability assessment and inference using Bayesian networks , 1996, IEEE Trans. Syst. Man Cybern. Part A.

[6]  Mark A. Peot,et al.  Automated Decision-Analytic Diagnosis of Thermal Performance in Gas Turbines , 1992 .

[7]  David Heckerman,et al.  Decision-theoretic troubleshooting , 1995, CACM.

[8]  Judea Pearl,et al.  Probabilistic Evaluation of Counterfactual Queries , 1994, AAAI.

[9]  Judea Pearl,et al.  From Conditional Oughts to Qualitative Decision Theory , 1993, UAI.

[10]  Moisés Goldszmidt,et al.  Action Networks: A Framework for Reasoning about Actions and Change under Uncertainty , 1994, UAI.

[11]  Don N. Kleinmuntz,et al.  Cognitive Heuristics and Feedback in a Dynamic Decision Environment , 1985 .

[12]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[13]  Michael R. Genesereth,et al.  The Use of Design Descriptions in Automated Diagnosis , 1984, Artif. Intell..

[14]  A. H. Murphy,et al.  Hailfinder: A Bayesian system for forecasting severe weather , 1996 .

[15]  Sampath Srinivas,et al.  A Generalization of the Noisy-Or Model , 1993, UAI.

[16]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[17]  Ward Edwards,et al.  Probabilistic Information Processing Systems: Design and Evaluation , 1968, IEEE Trans. Syst. Sci. Cybern..

[18]  Ward Edwards,et al.  Dynamic Decision Theory and Probabilistic Information Processings1 , 1962 .