Involutory Negator of Basic Belief Assignments

Dezert, Jean; Tchamova, Albena

doi:10.2478/cait-2023-0021

Abstract

This paper analyzes the different definitions of a negator of a probability mass function (pmf) and a Basic Belief Assignment (BBA) available in the literature. To overcome their limitations we propose an involutory negator of BBA, and we present a new indirect information fusion method based on this negator which can simplify the conflict management problem. The direct and indirect information fusion strategies are analyzed for three interesting examples of fusion of two BBAs. We also propose two methods for using the whole available information (the original BBAs and their negators) for decision-making support. The first method is based on the combination of the direct and indirect fusion strategies, and the second method selects the most reasonable fusion strategy to apply (direct, or indirect) based on the maximum entropy principle.

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Involutory Negator of Basic Belief Assignments

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