【摘要】 <正> 基于概率知识表达的信度网,已成为人工智能非精确知识表达与推理领域近10几年来研究的热点。目前国外的许多研究机构都对信度网进行了深入的研究。这些研究主要集中在以下三个方面:基于信度网的推理、基于信度网的学习和基于信度网的应用。其中基于信度网的推理一般分为:精确推理(即精确计算概率更多还原

【Abstract】 Belief network(BN) ,as a kind of knowledge representation based on the probabilistic theory, has become the main branch in the area of non-deterministic knowledge representation and inference in artificial intelligence (AI) in this decade. BN is being applied in many areas such as industry, military, medical treatment, commerce and so on ,and its representative systems involve expert system, voice recognition,fault diagnosis in space crafts,causality mining based on probabilistic syntax,etc. This paper introduces the primary methods and the current problems in inference of BN. After the introduction of the concept ,representation and goal of inference of BN,the paper summarizes the basic idea and problems in the principal algorithms of exact inference in BN,which include polytree propagation algorithm, clique tree propagation algorithm, graph reduction algorithm, and combination and optimization algorithm.更多还原