Proceedings

A Theory of Meta-Diagnosis: Reasoning about Diagnostic Systems

Download BibTeX Cite

Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 731-736.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-129

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.

Nuno Belard, Yannick Pencolé, and Michel Combacau. 2011. A Theory of Meta-Diagnosis: Reasoning about Diagnostic Systems. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 731–736. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-129
Welcome Future Conferences AI Journal Division IJCAI Proceedings About IJCAI IJCAI Awards