Uncertainty in Artificial Intelligence
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A Logic for Reasoning about Upper Probabilities
Joseph Halpern, Riccardo Pucella
Abstract:
We present a propositional logic 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.
Keywords:
Pages: 203-210
PS Link: http://www.cs.cornell.edu/home/halpern/papers/upjair.ps
PDF Link: /papers/01/p203-halpern.pdf
BibTex:
@INPROCEEDINGS{Halpern01,
AUTHOR = "Joseph Halpern and Riccardo Pucella",
TITLE = "A Logic for Reasoning about Upper Probabilities",
BOOKTITLE = "Proceedings of the Seventeenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-01)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2001",
PAGES = "203--210"
}


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