期刊名称：International Journal of Mathematics and Mathematical Sciences
印刷版ISSN：0161-1712
电子版ISSN：1687-0425
出版年度：2011
卷号：2011
DOI：10.1155/2011/845398
出版社：Hindawi Publishing Corporation
摘要：Bayesian Networks are graphic probabilistic models through
which we can acquire, capitalize on, and exploit knowledge. they are becoming
an important tool for research and applications in artificial intelligence
and many other fields in the last decade. This paper presents
Bayesian networks and discusses the inference problem in such models. It
proposes a statement of the problem and the proposed method to compute
probability distributions. It also uses D-separation for simplifying
the computation of probabilities in Bayesian networks. Given a Bayesian
network over a family 𝐼 of random variables, this paper presents a result
on the computation of the probability distribution of a subset 𝑆 of 𝐼
using separately a computation algorithm and D-separation properties.
It also shows the uniqueness of the obtained result.
