Diagnostic reasoning based on structure and behavior
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
A theory of diagnosis from first principles
Artificial Intelligence
Artificial Intelligence
Characterizing diagnoses and systems
Artificial Intelligence
Building problem solvers
Diagnosis of discrete-event systems from uncertain temporal observations
Artificial Intelligence
Model-Based Reasoning: Troubleshooting
Model-Based Reasoning: Troubleshooting
A theory of diagnosis for incomplete causal models
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
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In Model-Based Diagnosis, a diagnostic algorithm is typically used to compute diagnoses using a model of a real-world system and some observations. Contrary to classical hypothesis, in real-world applications it is sometimes the case that either the model, the observations or the diagnostic algorithm are abnormal with respect to some required properties; with possibly huge economical consequences. Determining which abnormalities exist constitutes a meta-diagnostic problem. We contribute, first, with a general theory of meta-diagnosis with clear semantics to handle this problem. Second, we propose a series of typically required properties and relate them between themselves. Finally, using our meta-diagnostic framework and the studied properties and relations, we model and solve some common meta-diagnostic problems.