The Generalized Pignistic Transformation

Jean Dezert · Florentín Smarandache · Milan Daniel

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Multi-Criteria Decision Making Fuzzy and Soft Set Theory Advanced Mathematical Theories

Abstract

This paper presents in detail the generalized pignistic transformation (GPT) succinctly developed in the Dezert-Smarandache Theory (DSmT) framework as a tool for decision process. The GPT allows to provide a subjective probability measure from any generalized basic belief assignment given by any corpus of evidence. We mainly focus our presentation on the 3D case and provide the complete result obtained by the GPT and its validation drawn from the probability theory.

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References

2000Data fusion in the transferable belief model 2020Advances and Applications of DSmT for Information Fusion : Collected Works

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2006On transformations of belief functions to probabilities 2005Probabilistic Transformations of Belief Functions 2008Implementing general belief function framework with a practical codification for low complexity

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