Imaginary Kinematics

TL;DR

This paper introduces a new belief adjustment method called Imaginary Kinematics, extending Lewis' imaging to probabilistic evidence, capable of handling inconsistent information while satisfying belief revision postulates.

Contribution

It proposes a novel class of belief adjustment rules extending Lewis' imaging to probabilistic and inconsistent evidence scenarios.

Findings

The proposed rules generalize belief revision to handle inconsistent information.

They satisfy standard belief revision postulates under certain conditions.

The method is based on an imaginary counterpart of probability kinematics.

Abstract

We introduce a novel class of adjustment rules for a collection of beliefs. This is an extension of Lewis' imaging to absorb probabilistic evidence in generalized settings. Unlike standard tools for belief revision, our proposal may be used when information is inconsistent with an agent's belief base. We show that the functionals we introduce are based on the imaginary counterpart of probability kinematics for standard belief revision, and prove that, under certain conditions, all standard postulates for belief revision are satisfied.