Semigraphoids Are Two-Antecedental Approximations of Stochastic Conditional Independence Models
Artificial Intelligence
2013-02-28 v1
Abstract
The semigraphoid closure of every couple of CI-statements (GI=conditional independence) is a stochastic CI-model. As a consequence of this result it is shown that every probabilistically sound inference rule for CI-model, having at most two antecedents, is derivable from the semigraphoid inference rules. This justifies the use of semigraphoids as approximations of stochastic CI-models in probabilistic reasoning. The list of all 19 potential dominant elements of the mentioned semigraphoid closure is given as a byproduct.
Keywords
Cite
@article{arxiv.1302.6847,
title = {Semigraphoids Are Two-Antecedental Approximations of Stochastic Conditional Independence Models},
author = {Milan Studeny},
journal= {arXiv preprint arXiv:1302.6847},
year = {2013}
}
Comments
Appears in Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI1994)