A Probabilistic Approach to Hierarchical Model-based Diagnosis
Artificial Intelligence
2013-02-28 v1
Abstract
Model-based diagnosis reasons backwards from a functional schematic of a system to isolate faults given observations of anomalous behavior. We develop a fully probabilistic approach to model based diagnosis and extend it to support hierarchical models. Our scheme translates the functional schematic into a Bayesian network and diagnostic inference takes place in the Bayesian network. A Bayesian network diagnostic inference algorithm is modified to take advantage of the hierarchy to give computational gains.
Cite
@article{arxiv.1302.6846,
title = {A Probabilistic Approach to Hierarchical Model-based Diagnosis},
author = {Sampath Srinivas},
journal= {arXiv preprint arXiv:1302.6846},
year = {2013}
}
Comments
Appears in Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI1994)