基于D-S证据理论的多智能体系统冲突数据融合机制研究  

Research on mechanism of conflict data fusion in multi-agent systems based on D-S evidence theory

作　　者：王娜[1] 刘静渝 李皓然 夏晓峰[2] WANG Na;LIU Jingyu;LI Haoran;XIA Xiaofeng(College of Mathematics and Computer Science,Hengshui University,Hengshui,Hebei 053000,P.R.China;School of Bigdata and Software Engineering,Chongqing University,Chongqing 400044,P.R.China;29th Research Institute of China Electronics Technology Group Corporation,Chengdu 610036,P.R.China)

机构地区：[1]衡水学院数学与计算机科学学院,河北衡水053000 [2]重庆大学大数据与软件学院,重庆400044 [3]中国电子科技集团公司第二十九研究所,成都610036

出　　处：《重庆大学学报》2025年第2期22-34,共13页Journal of Chongqing University

基　　金：成都市区域科技创新合作项目(2023-YF11-00018-HZ);国家自然科学基金(62372075)。

摘　　要：多智能体信息融合(multi-agent information fusion,MAIF)系统主要面向多个智能体之间的信息融合、调节、交流和矛盾处理。研究针对数据高度冲突条件下的D-S证据理论失效问题,提出一种将重构的基本概率分配和信念熵相结合的多智能体系统冲突数据融合方法。该方法使用重构的基本概率分配和信念熵修正证据的可靠性,获得更合理的证据,使用Dempster组合规则将证据进行融合得到结果,在2个实验中均得到了超过90%的置信度。实验表明了该方法的有效性,提高了MAIF系统辨识过程的精度。The multi-agent information fusion(MAIF)system is smainly aimed at information fusion,regulation,communication,and conflict resolution among multiple agents.A multi-agent system conflict data fusion method combining reconstructed basic probability assignment and belief entropy is proposed to address the issue of D-S evidence theory failure under highly conflicting data conditions.This method uses reconstructed basic probability assignment and belief entropy to correct the reliability of evidence,obtaining more reasonable evidence.Then,the evidence is fused using the Dempster combination rule,and the results are obtained with a confidence level of over 90%in both 2 experiments.The experiment demonstrates the effectiveness of this method and improves the accuracy of the MAIF system identification process.

关 键 词：基本概率分配 熵 D-S证据理论 多智能体 信息融合 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]