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and inference. Real-world problems are modeled in this framework by a network of interrelated entities, called variables. The relationships between variables (possibly uncertain or imprecise) are represented by the functions called valuations. The two basic operations for performing inference in a
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VBS are combination and marginalization. Combination corresponds to the aggregation of knowledge, while marginalization refers to the focusing (coarsening) of it. VBSs were introduced by
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of the topic and provide significant coverage of it beyond a mere trivial mention. If notability cannot be shown, the article is likely to be
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Shenoy, Prakash P. Valuation based systems: A framework for managing uncertainty in expert systems. In L. A. Zadeh and J. Kacprzyk, editors,
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Shenoy, Prakash P. and Shafer, G. Axioms for probability and belief-function propagation. In J. Pearl G. Shafer, editor,
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VBS are used for knowledge representation in expert systems and data fusion.
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Shenoy, Prakash P. A valuation-based language for expert systems.
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Please help to demonstrate the notability of the topic by citing
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in 1989 as general frameworks for managing uncertainty in
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