Evidence as Opinions of Experts

TL;DR

This paper offers a new interpretation of Dempster/Shafer theory by modeling it as a statistical aggregation of expert opinions, simplifying the combination process through homomorphic mappings.

Contribution

It introduces simpler spaces for evidence combination that are easier to interpret and implement, connecting Bayesian opinions with Dempster/Shafer theory.

Findings

Spaces with binary operations can be mapped onto Dempster/Shafer space

Experts combine evidence using Bayesian methods in these spaces

Alternative spaces for evidence combination are proposed

Abstract

We describe a viewpoint on the Dempster/Shafer 'Theory of Evidence', and provide an interpretation which regards the combination formulas as statistics of the opinions of "experts". This is done by introducing spaces with binary operations that are simpler to interpret or simpler to implement than the standard combination formula, and showing that these spaces can be mapped homomorphically onto the Dempster/Shafer theory of evidence space. The experts in the space of "opinions of experts" combine information in a Bayesian fashion. We present alternative spaces for the combination of evidence suggested by this viewpoint.