FUSION, PROPAGATION, AND STRUCTURING IN BELIEF NETWORKS
FUSION, PROPAGATION, AND STRUCTURING IN BELIEF NETWORKS
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DOI：
10.1016/0004-3702(86)90072-x
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发表时间：
1986-09-01
影响因子：
14.4
通讯作者：
PEARL, J
中科院分区：
文献类型：
--
作者：
PEARL, J
信念网络是有向无环图，其中节点表示命题（或变量），弧表示链接命题之间的直接依赖关系，这些依赖关系的强度由条件概率量化。这种网络可以用来表示领域专家的一般知识，如果这些链接不仅用于存储事实知识，而且还用于指导和激活操纵这些知识的计算中的数据流，那么它就变成了一个计算体系结构。本文的第一部分讨论了在这样的网络中融合和传播新信息的影响的任务。这样，当达到平衡时，每个命题都会被赋予与概率论公理相一致的信念。它表明，如果网络是单连接的（如树结构），那么概率可以通过并行和自治处理器的同构网络中的局部传播来更新，并且新信息的影响可以与网络中最长路径成比例地及时传递给所有命题。本文的第二部分讨论了利用辅助算子为一组概率耦合命题寻找树结构表示的问题。
Belief networks are directed acyclic graphs in which the nodes represent propositions (or variables), the arcs signify direct dependencies between the linked propositions, and the strengths of these dependencies are quantified by conditional probabilities. A network of this sort can be used to represent the generic knowledge of a domain expert, and it turns into a computational architecture if the links are used not merely for storing fac tual knowledge but also for directing and activating the data flow in the computations which manipulate this knowledge.The first part of the paper deals with the task of fusing and propagating the impacts of new information through the networks in such a way that, when equilibrium is reached, eachpropositionwillbeassignedameasureofbeliefconsistentwiththeaxiomsofproba bilitytheory. Itisshownthatifthenetworkissinglyconnected (eg tree-structured), then probabilities can be updated by local propagation in an isomorphic network of parallel and autonomous processors and that the impact of new information can be imparted to all propositions in time proportional to the longest path in the network. The second part of the paper deals with the problem of finding a tree-structured representation for a collection of probabilistically coupled propositions using auxiliary