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. © 2006 AI Access Foundation. All rights reserved.
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CITATION STYLE
Halpern, J. Y., & Pucella, R. (2006). A logic for reasoning about evidence. Journal of Artificial Intelligence Research, 26, 1–34. https://doi.org/10.1613/jair.1838
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