Conflict-based diagnosis: adding uncertainty to model-based diagnosis

Consistency-based diagnosis concerns using a model of the structure and behaviour of a system in order to analyse whether or not the system is malfunctioning. A well-known limitation of consistency-based diagnosis is that it is unable to cope with uncertainty. Uncertainty reasoning is nowadays done using Bayesian networks. In this field, a conflict measure has been introduced to detect conflicts between a given probability distribution and associated data. In this paper, we use a probabilistic theory to represent logical diagnostic systems and show that in this theory we are able to determine consistent and inconsistent states as traditionally done in consistency-based diagnosis. Furthermore, we analyse how the conflict measure in this theory offers a way to favour particular diagnoses above others. This enables us to add uncertainty reasoning to consistency-based diagnosis in a seamless fashion.

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

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

[3]  A. Hasman,et al.  Probabilistic reasoning in intelligent systems: Networks of plausible inference , 1991 .

[4]  Pietro Torasso,et al.  On the Relationship between Abduction and Deduction , 1991, J. Log. Comput..

[5]  Peter J. F. Lucas.  Bayesian model-based diagnosis , 2001, Int. J. Approx. Reason..

[6]  Franz Wotawa,et al.  Introducing Alias Information into Model-Based Debugging , 2004, ECAI.

[7]  Johan de Kleer,et al.  Using Crude Probability Estimates to Guide Diagnosis , 1990, Artif. Intell..

[8]  Peter Struss,et al.  Model-Based Systems in the Automotive Industry , 2004, AI Mag..

[9]  Finn V. Jensen,et al.  Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.

[10]  Raymond Reiter,et al.  A Theory of Diagnosis from First Principles , 1986, Artif. Intell..

[11]  David Poole,et al.  Probabilistic Conflicts in a Search Algorithm for Estimating Posterior Probabilities in Bayesian Networks , 1996, Artif. Intell..

[12]  Raymond Reiter,et al.  Characterizing Diagnoses and Systems , 1992, Artif. Intell..

[13]  S. E. Ahmed,et al.  Bayesian Networks and Decision Graphs , 2008, Technometrics.

[14]  Jürg Kohlas,et al.  Model-Based Diagnostics and Probabilistic Assumption-Based Reasoning , 1998, Artif. Intell..