English

Implementing general belief function framework with a practical codification for low complexity

Artificial Intelligence 2008-07-23 v1

Abstract

In this chapter, we propose a new practical codification of the elements of the Venn diagram in order to easily manipulate the focal elements. In order to reduce the complexity, the eventual constraints must be integrated in the codification at the beginning. Hence, we only consider a reduced hyper power set DrΘD_r^\Theta that can be 2Θ2^\Theta or DΘD^\Theta. We describe all the steps of a general belief function framework. The step of decision is particularly studied, indeed, when we can decide on intersections of the singletons of the discernment space no actual decision functions are easily to use. Hence, two approaches are proposed, an extension of previous one and an approach based on the specificity of the elements on which to decide. The principal goal of this chapter is to provide practical codes of a general belief function framework for the researchers and users needing the belief function theory.

Cite

@article{arxiv.0807.3483,
  title  = {Implementing general belief function framework with a practical codification for low complexity},
  author = {Arnaud Martin},
  journal= {arXiv preprint arXiv:0807.3483},
  year   = {2008}
}

Comments

Advances and Applications of DSmT for Information Fusion, Florentin Smarandache & Jean Dezert (Ed.) (2008) Pnd

R2 v1 2026-06-21T11:03:07.905Z