Defaults and Infinitesimals: Defeasible Inference by Nonarchimedean Entropy-Maximization
arXiv:1302.4988
Abstract
We develop a new semantics for defeasible inference based on extended probability measures allowed to take infinitesimal values, on the interpretation of defaults as generalized conditional probability constraints and on a preferred-model implementation of entropy maximization.
Appears in Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence (UAI1995)