A method for managing evidential reasoning in a hierarchical hypothesis space
Artificial Intelligence
A theory of diagnosis from first principles
Artificial Intelligence
IEEE Transactions on Systems, Man and Cybernetics - Special issue on artificial intelligence
Using crude probability estimates to guide diagnosis
Artificial Intelligence
Modeling digital circuits for troubleshooting
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
AI Communications
A spectrum of logical definitions of model-based diagnosis
Computational Intelligence
Diagnostic reasoning across different time points
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Temporal constraint satisfaction on causal models
Information Sciences: an International Journal
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Probability and Statistics with Reliability, Queuing and Computer Science Applications
Probability and Statistics with Reliability, Queuing and Computer Science Applications
A diagnosis method of dynamic system using the knowledge on system description
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
Normality and faults in logic-based diagnosis
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Diagnosis with behavioral modes
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
MUNIN: a causal probabilistic network for interpretation of electromyographic findings
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
An improved constraint-propagation algorithm for diagnosis
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
Integrating model-based monitoring and diagnosis of complex dynamic systems
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
Representing diagnostic knowledge for probabilistic Horn abduction
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
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Although the notion of diagnostic problem has been extensively investigated in the context of static systems, in most practical applications the behavior of the modeled system is significantly variable during time. The goal of the paper is to propose a novel approach to the modeling of uncertainty about temporal evolutions of time-varying systems and a characterization of model-based temporal diagnosis. Since in most real world cases knowledge about the temporal evolution of the system to be diagnosed is uncertain, we consider the case when probabilistic temporal knowledge is available for each component of the system and we choose to model it by means of Markov chains. In fact, we aim at exploiting the statistical assumptions underlying reliability theory in the context of the diagnosis of time-varying systems. We finally show how to exploit Markov chain theory in order to discard, in the diagnostic process, very unlikely diagnoses.