Imaginary Kinematics
This addresses a limitation in standard belief revision tools for agents dealing with inconsistent information, though it appears incremental as an extension of existing concepts.
The paper tackles the problem of belief revision when new information is inconsistent with an agent's existing beliefs by introducing a novel class of adjustment rules based on an extension of Lewis' imaging. It proves that under certain conditions, these rules satisfy all standard postulates for belief revision.
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.