Evidence Absorption and Propagation through Evidence Reversals
Artificial Intelligence
2013-04-08 v1
Abstract
The arc reversal/node reduction approach to probabilistic inference is extended to include the case of instantiated evidence by an operation called "evidence reversal." This not only provides a technique for computing posterior joint distributions on general belief networks, but also provides insight into the methods of Pearl [1986b] and Lauritzen and Spiegelhalter [1988]. Although it is well understood that the latter two algorithms are closely related, in fact all three algorithms are identical whenever the belief network is a forest.
Keywords
Cite
@article{arxiv.1304.1525,
title = {Evidence Absorption and Propagation through Evidence Reversals},
author = {Ross D. Shachter},
journal= {arXiv preprint arXiv:1304.1525},
year = {2013}
}
Comments
Appears in Proceedings of the Fifth Conference on Uncertainty in Artificial Intelligence (UAI1989)