2003/07/30 by Joseph Y. Halpern, Riccardo Pucella
Computer Science · #cs.AI #cs.LO
published as Journal of AI Research 17, 2001, pp. 57-81 · A preliminary version of this paper appeared in Proc. of the 17th Conference on Uncertainty in AI, 2001
arxiv created 2003/07/30 · arxiv updated 2009/12/01
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.