ArticleIEEE transactions on cybernetics2016
Evidence Combination From an Evolutionary Game Theory Perspective.
Article in IEEE transactions on cybernetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Article
- Evolutionary game theory and simulations based on doctor and patient medical malpractice.PloS one · 2023Article
- A Networked Method for Multi-Evidence-Based Information Fusion.Entropy (Basel, Switzerland) · 2022Article
- Multi-Source Information Fusion Based on Negation of Reconstructed Basic Probability Assignment with Padded Gaussian Distribution and Belief Entropy.Entropy (Basel, Switzerland) · 2022Article
- Local Trust in Internet of Things Based on Contract Theory.Sensors (Basel, Switzerland) · 2022Article
- Evolutionary game analysis of environmental pollution control under the government regulation.Scientific reports · 2022Article
- An Evolutionary Game-Theoretic Approach for Assessing Privacy Protection in mHealth Systems.International journal of environmental research and public health · 2018Article
- A dynamic discount pricing strategy for viral marketing.PloS one · 2018Article
- Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method.Sensors (Basel, Switzerland) · 2017Article
- A Reliability-Based Method to Sensor Data Fusion.Sensors (Basel, Switzerland) · 2017Article
- Zero-Sum Matrix Game with Payoffs of Dempster-Shafer Belief Structures and Its Applications on Sensors.Sensors (Basel, Switzerland) · 2017Article
- Sensing Attribute Weights: A Novel Basic Belief Assignment Method.Sensors (Basel, Switzerland) · 2017Article
- Evaluation of university scientific research ability based on the output of sci-tech papers: A D-AHP approach.PloS one · 2017Article
- Article
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Authors and funding
5 authors.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.