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The goal of this article is to study the connection between the Dempster-Shafter theory (DST) and probabilistic argumentation systems (PASs). By introducing a general method to translate PASs into corresponding Dempster-Shafter belief potentials, its contribution is twofold. On the one hand, the article proposes PASs as a convenient and powerful modeling language to be put on top of the DST. On the other hand, it shows how to use the DST as an efficient computational tool for numerical computations in PASs.

This article discusses several implementation aspects for Dempster-Shafer belief functions. The main objective is to propose an appropriate representation of mass functions and efficient data structures and algorithms for the two basic operations of combination and marginalization.

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