Exploiting Uncertain and Temporal Information in Correlation
Artificial Intelligence
2013-02-08 v1
Abstract
A modelling language is described which is suitable for the correlation of information when the underlying functional model of the system is incomplete or uncertain and the temporal dependencies are imprecise. An efficient and incremental implementation is outlined which depends on cost functions satisfying certain criteria. Possibilistic logic and probability theory (as it is used in the applications targetted) satisfy these criteria.
Cite
@article{arxiv.1302.1521,
title = {Exploiting Uncertain and Temporal Information in Correlation},
author = {John Bigham},
journal= {arXiv preprint arXiv:1302.1521},
year = {2013}
}
Comments
Appears in Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (UAI1997)