Evidence Combination from an Evolutionary Game Theory Perspective

Xinyang Deng, Deqiang Han, Jean Dezert, Yong Deng, Yu Shyr

研究成果: Article同行評審

152 引文 斯高帕斯(Scopus)

摘要

Dempster-Shafer evidence theory is a primary methodology for multisource information fusion because it is good at dealing with uncertain information. This theory provides a Dempster's rule of combination to synthesize multiple evidences from various information sources. However, in some cases, counter-intuitive results may be obtained based on that combination rule. Numerous new or improved methods have been proposed to suppress these counter-intuitive results based on perspectives, such as minimizing the information loss or deviation. Inspired by evolutionary game theory, this paper considers a biological and evolutionary perspective to study the combination of evidences. An evolutionary combination rule (ECR) is proposed to help find the most biologically supported proposition in a multievidence system. Within the proposed ECR, we develop a Jaccard matrix game to formalize the interaction between propositions in evidences, and utilize the replicator dynamics to mimick the evolution of propositions. Experimental results show that the proposed ECR can effectively suppress the counter-intuitive behaviors appeared in typical paradoxes of evidence theory, compared with many existing methods. Properties of the ECR, such as solution's stability and convergence, have been mathematically proved as well.

原文English
文章編號7194765
頁(從 - 到)2070-2082
頁數13
期刊IEEE Transactions on Cybernetics
46
發行號9
DOIs
出版狀態Published - 2016 9月

All Science Journal Classification (ASJC) codes

  • 軟體
  • 控制與系統工程
  • 資訊系統
  • 人機介面
  • 電腦科學應用
  • 電氣與電子工程

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