Combining belief functions issued from dependent sources

Marco Cattaneo

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Multi-Criteria Decision Making Logic, Reasoning, and Knowledge Bayesian Modeling and Causal Inference

Abstract

Dempster's rule for combining two belief functions assumes the independence of the sources of information.If this assumption is questionable, I suggest to use the least specific combination minimizing the conflict among the ones allowed by a simple generalization of Dempster's rule.This increases the monotonicity of the reasoning and helps us to manage situations of dependence.Some properties of this combination rule and its usefulness in a generalization of Bayes' theorem are then considered.

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References

1990The combination of evidence in the transferable belief model 1998Uncertainty-Based Information: Elements of Generalized Information Theory 1986On the unicity of dempster rule of combination 1992The Dynamic of Belief in the transferable belief model and Specialization-Generalization Matrices

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2010Belief functions combination without the assumption of independence of the information sources 2006On the independence requirement in Dempster-Shafer theory for combining classifiers providing statistical evidence 2014The choice of generalized Dempster–Shafer rules for aggregating belief functions

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