Cautious Propagation in Bayesian Networks
Artificial Intelligence
2013-02-21 v1
Abstract
Consider the situation where some evidence e has been entered to a Bayesian network. When performing conflict analysis, sensitivity analysis, or when answering questions like "What if the finding on X had been y instead of x?" you need probabilities P (e'| h), where e' is a subset of e, and h is a configuration of a (possibly empty) set of variables. Cautious propagation is a modification of HUGIN propagation into a Shafer-Shenoy-like architecture. It is less efficient than HUGIN propagation; however, it provides easy access to P (e'| h) for a great deal of relevant subsets e'.
Keywords
Cite
@article{arxiv.1302.4962,
title = {Cautious Propagation in Bayesian Networks},
author = {Finn Verner Jensen},
journal= {arXiv preprint arXiv:1302.4962},
year = {2013}
}
Comments
Appears in Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence (UAI1995)