Jeffrey's rule of conditioning generalized to belief functions

TL;DR

This paper generalizes Jeffrey's rule of conditioning within belief function models, connecting it to geometrical and Dempster's conditioning rules, thereby broadening its applicability in belief revision.

Contribution

It introduces generalized forms of Jeffrey's conditioning for belief functions, linking them to existing geometrical and Dempster's rules.

Findings

Multiple forms of Jeffrey's conditioning are defined for belief functions.

These forms correspond to geometrical and Dempster's conditioning rules.

The generalization enhances belief revision methods in uncertain reasoning.

Abstract

Jeffrey's rule of conditioning has been proposed in order to revise a probability measure by another probability function. We generalize it within the framework of the models based on belief functions. We show that several forms of Jeffrey's conditionings can be defined that correspond to the geometrical rule of conditioning and to Dempster's rule of conditioning, respectively.