A Theory of Meta-Diagnosis: Reasoning About Diagnostic Systems
Abstract
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.
Cite
Text
Belard et al. "A Theory of Meta-Diagnosis: Reasoning About Diagnostic Systems." International Joint Conference on Artificial Intelligence, 2011. doi:10.5591/978-1-57735-516-8/IJCAI11-129Markdown
[Belard et al. "A Theory of Meta-Diagnosis: Reasoning About Diagnostic Systems." International Joint Conference on Artificial Intelligence, 2011.](https://mlanthology.org/ijcai/2011/belard2011ijcai-theory/) doi:10.5591/978-1-57735-516-8/IJCAI11-129BibTeX
@inproceedings{belard2011ijcai-theory,
title = {{A Theory of Meta-Diagnosis: Reasoning About Diagnostic Systems}},
author = {Belard, Nuno and Pencolé, Yannick and Combacau, Michel},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2011},
pages = {731-737},
doi = {10.5591/978-1-57735-516-8/IJCAI11-129},
url = {https://mlanthology.org/ijcai/2011/belard2011ijcai-theory/}
}