Abstract
This short note studies a multiple source extension of categorical mass functions in the sense of Shafer’s evidence theory. Each subset of possible worlds is associated with a subset of information sources and represents a tentative description of what is known. Analogs of belief, plausibility, commonality functions, valued in terms of subsets of agents or sources, are defined, replacing summation by set union. Set-valued plausibility is nothing but set-valued possibility because it is union-decomposable with respect to the union of events. In a special case where each source refers to a single information item, set-valued belief functions decompose with respect to intersection and are thus multiple source necessity-like function. Connections with Belnap epistemic truth-values for handling multiple source inconsistent information are shown. A formal counterpart of Dempster rule of combination is defined and discussed as to its merits for information fusion.
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Dubois, D., Prade, H. (2017). A Set-Valued Approach to Multiple Source Evidence. In: Benferhat, S., Tabia, K., Ali, M. (eds) Advances in Artificial Intelligence: From Theory to Practice. IEA/AIE 2017. Lecture Notes in Computer Science(), vol 10351. Springer, Cham. https://doi.org/10.1007/978-3-319-60045-1_14
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DOI: https://doi.org/10.1007/978-3-319-60045-1_14
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