Conditional probabilistic reasoning without conditional logic

Imaging is a class of non-Bayesian methods for the revision of probability density functions originally proposed as a semantics for conditional logic. Two of this revision functions, Standard Imaging and General Imaging have successfully been applied to modelling information retrieval (IR). Due to the problematic nature of a "direct" implementation of Imaging revision functions, we propose thei alternative implementaion by representing the semantic structure that underlies them, in the language of a probalistic (Bayesian) logic. Recasting this models of information retrieval in such a general-purpose Knowledge representation (KR) tool, be sides showing the potential of this "Bayesian" tool for the representation of non-Bayesian revision functions, paves the way to a possible integration of this models with other more KR-oriented modes of IR, and to the exploitation of general purpose domain-knowledge.