Definition of evidence fusion rules on the basis of Referee Functions

TL;DR

This paper introduces a novel framework for evidence fusion rules using referee functions, enabling algorithmic implementation and versatile rule construction without complex mathematics.

Contribution

It presents a new referee function-based framework for evidence fusion, including a sampling method that simplifies rule definition and allows for the creation of new, consensus-aware fusion rules.

Findings

Framework successfully implements various known evidence rules.

Sampling method reduces combinatorial complexity.

New evidence fusion rules incorporate source consensus.

Abstract

This chapter defines a new concept and framework for constructing fusion rules for evidences. This framework is based on a referee function, which does a decisional arbitrament conditionally to basic decisions provided by the several sources of information. A simple sampling method is derived from this framework. The purpose of this sampling approach is to avoid the combinatorics which are inherent to the definition of fusion rules of evidences. This definition of the fusion rule by the means of a sampling process makes possible the construction of several rules on the basis of an algorithmic implementation of the referee function, instead of a mathematical formulation. Incidentally, it is a versatile and intuitive way for defining rules. The framework is implemented for various well known evidence rules. On the basis of this framework, new rules for combining evidences are proposed, which takes into account a consensual evaluation of the sources of information.