Conflict management in information fusion with belief functions
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Abstract (arXiv)
In Information fusion, the conflict is an important concept. Indeed, combining several imperfect experts or sources allows conflict. In the theory of belief functions, this notion has been discussed a lot. The mass appearing on the empty set during the conjunctive combination rule is generally considered as conflict, but that is not really a conflict. Some measures of conflict have been proposed and some approaches have been proposed in order to manage this conflict or to decide with conflicting mass functions. We recall in this chapter some of them and we propose a discussion to consider the conflict in information fusion with the theory of belief functions.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Sep 2017.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 1; 2025: 1.
5 papers.
- 2024Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusioncited by 4
- 2023Estimation of the qualification and behavior of a contributor and aggregation of his answers in a crowdsourcing contextcited by 1
- 2023Evidential uncertainty sampling for active learningcited by 1
- 2022Belief functions on ordered frames of discernmentcited by 0
- 2025Resolving Zadehs Paradox Axiomatic Possibility Theory as a Foundation for Reliable Artificial Intelligencecited by 0
- 2025Resolving Zadehs Paradox Axiomatic Possibility Theory as a Foundation for Reliable Artificial Intelligence4 Dec 2025
- 2024Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion23 Dec 2024
- 2023Evidential uncertainty sampling for active learning21 Sep 2023
- 2023Estimation of the qualification and behavior of a contributor and aggregation of his answers in a crowdsourcing context8 Mar 2023
- 2022Belief functions on ordered frames of discernment10 Oct 2022