Uncertainty in Artificial Intelligence
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A Logic for Reasoning about Evidence
Joseph Halpern, Riccardo Pucella
We introduce a logic for reasoning about evidence, that essentially views evidence as a function from prior beliefs (before making an observation) to posterior beliefs (after making the observation). We provide a sound and complete axiomatization for the logic, and consider the complexity of the decision problem. Although the reasoning in the logic is mainly propositional, we allow variables representing numbers and quantification over them. This expressive power seems necessary to capture important properties of evidence
Pages: 297-304
PS Link: http://www.cs.cornell.edu/home/halpern/papers/evidence.ps
PDF Link: /papers/03/p297-halpern.pdf
AUTHOR = "Joseph Halpern and Riccardo Pucella",
TITLE = "A Logic for Reasoning about Evidence",
BOOKTITLE = "Proceedings of the Nineteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-03)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2003",
PAGES = "297--304"

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