2013/03/13 by Carl Wagner, Carl G. Wagner, Wagner, Carl G.
Computer Science · Decision Sciences · Physics and Astronomy · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Multi-Criteria Decision Making #Statistical Mechanics and Entropy #cs.AI
paper · pdf · doi:10.48550/arxiv.1303.5436
Appears in Proceedings of the Eighth Conference on Uncertainty in Artificial Intelligence (UAI1992)
arxiv created 2013/03/13 · openalex publication_date 2013/03/13 · arxiv updated 2013/03/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Jeffrey's rule has been generalized by Wagner to the case in which new evidence bounds the possible revisions of a prior probability below by a Dempsterian lower probability. Classical probability kinematics arises within this generalization as the special case in which the evidentiary focal elements of the bounding lower probability are pairwise disjoint. We discuss a twofold extension of this generalization, first allowing the lower bound to be any two-monotone capacity and then allowing the prior to be a lower envelope.