A logic for reasoning about upper probabilities

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dc.creatorHalpern, Joseph Y.
dc.creatorPucella, Riccardo
dc.date2003-07-30
dc.date.accessioned2026-07-07T03:20:09Z
dc.date.available2026-07-07T03:20:09Z
dc.descriptionWe 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.
dc.descriptionA preliminary version of this paper appeared in Proc. of the 17th Conference on Uncertainty in AI, 2001
dc.identifierhttps://arxiv.org/abs/cs/0307069
dc.identifierhttp://arxiv.org/abs/cs/0307069
dc.identifierJournal of AI Research 17, 2001, pp. 57-81
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/31729
dc.subjectArtificial Intelligence
dc.subjectLogic in Computer Science
dc.subjectI.2.4; F.2.1
dc.titleA logic for reasoning about upper probabilities
dc.typetext

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