多值动态不确定因果图的推理算法研究  

Research on Inference Algorithm of Multivalued Dynamic Uncertain Causality Graph

作　　者：郑海 王洪春 ZHENG Hai;WANG Hongchun(School of Mathematical Science,Chongqing Normal University,Chongqing 401331,China)

机构地区：[1]重庆师范大学数学科学学院,重庆401331

出　　处：《重庆师范大学学报（自然科学版）》2023年第4期107-116,共10页Journal of Chongqing Normal University:Natural Science

基　　金：国家社会科学基金一般项目(No.13BTJ008);重庆市教育委员会人文社会科学重点项目(No.22SKGH081);重庆市教育委员会重庆市高等教育教学改革研究项目(No.213139)。

摘　　要：利用领域知识求解多值动态不确定因果图的联合概率分布所涉及的领域因果图的概率分布表达式构造难度大,针对这一问题,从2类因果循环图出发,提出一种基于图分解的推理算法。该算法极大地简化了全局概率分布表达式的构造过程,有效地降低了领域因果图概率分布表达式构造的难度。提高了多值动态不确定因果图的推理效率。In order to solve the joint probability distribution of Multivalued Dynamic Uncertain Causality Graph with domain knowledge,it is difficult to construct the probability distribution expression of domain causal graphs.An inference algorithm based on graph decomposition is proposed from two kinds of cyclic causal graphs,which greatly simplifies the construction of global probability distribution expression,effectively reduces the difficulty of constructing probability distribution expression of domain causal graphs,and improves the inference efficiency of multi-valued dynamic uncertain causal graphs.

关 键 词：多值动态不确定因果图 有向循环图 推理算法 参数学习 概率推理 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]