The use of design descriptions in automated diagnosis
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
A theory of diagnosis from first principles
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Using crude probability estimates to guide diagnosis
Artificial Intelligence
Characterizing diagnoses and systems
Artificial Intelligence
Model-based diagnostics and probabilistic assumption-based reasoning
Artificial Intelligence
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Model-based systems in the automotive industry
AI Magazine
Combining Abduction with Conflict-based Diagnosis
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
The Probabilistic Interpretation of Model-Based Diagnosis
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Maximal-confirmation diagnoses
Knowledge-Based Systems
QoS-based probabilistic fault-diagnosis method for exception handling
ICWL'10 Proceedings of the 2010 international conference on New horizons in web-based learning
Sequential diagnosis by abstraction
Journal of Artificial Intelligence Research
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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.