用于态势评估中因果推理的贝叶斯网络

1 引言贝叶斯网络是由R.Howard和J.Matheson于1981年提出来的,它主要用来表述不确定的专家知识。后来经过J.Pearl,D.Heckerman等人的研究,贝叶斯网络的理论及算法有了很大的发展。作为一种知识表示和进行概率推理的框架,贝叶斯网络在具有内在不确定性的推理和决策问题中已经得到了广泛的应用,例如概率专家系统、计算机视觉和数据挖掘等。

Bayesian Networks for Causal Reasoning in Situation Assessment

Causal reasoning plays an important role in situation assessment (SA). Using Bayesian networks to find out the hidden patterns between situation hypothesis and events is the function needed to accomplish in situation as sessment. Based on different link relationship,a Bayesian network model for situation assessment is analyzed in this paper. To overcome the weakness of this model in application for dynamic changed scenario ,this paper presents an approach that uses a dynamic Bayesian network to represent features of the situation hypothesis and events. And the algorithms of propagation of corresponding information through the network are introduced respectively.