A logic for reasoning about upper probabilities
Artificial Intelligence
2007-05-23 v1 Logic in Computer Science
Abstract
We present a propositional logic %which can be used to reason about the uncertainty of events, where the uncertainty is modeled by a set of probability measures assigning an interval of probability to each event. We give a sound and complete axiomatization for the logic, and show that the satisfiability problem is NP-complete, no harder than satisfiability for propositional logic.
Cite
@article{arxiv.cs/0307069,
title = {A logic for reasoning about upper probabilities},
author = {Joseph Y. Halpern and Riccardo Pucella},
journal= {arXiv preprint arXiv:cs/0307069},
year = {2007}
}
Comments
A preliminary version of this paper appeared in Proc. of the 17th Conference on Uncertainty in AI, 2001