A logic for reasoning about evidence

Authors:
Joseph Y. Halpern;Riccardo Pucella
Affiliations:
Department of Computer Science, Cornell University, Ithaca, NY;Department of Computer Science, Cornell University, Ithaca, NY
Venue:
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Year:
2002

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Abstract

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.