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Decision Rules Under Vague and Uncertain Information

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Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 394))

Abstract

A decision processes in presence of uncertainty and fuzziness can be performed by using the interpretation of a fuzzy set as a pair whose elements are a suitable crisp event \(E_\varphi \) of the kind “You claim that the variable X has the property \(\varphi \)” and an assessment consistent with an uncertainty conditional measure on the conditional events \(E_\varphi |\{X=x\}\). The decision framework is based on uncertain fuzzy IF-THEN rules performed through the concept of degree of implication between two “fuzzy events”, expressed by a conditional uncertainty measure.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Sciences, via Vanvitelli, 1, 06123, Perugia, Italy

    Giulianella Coletti

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  1. Giulianella Coletti
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Correspondence to Giulianella Coletti .

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Editors and Affiliations

  1. Sorbonne Université, CNRS, LIP6, Paris, France

    Marie-Jeanne Lesot

  2. Sorbonne Université, CNRS, LIP6, Paris, France

    Christophe Marsala

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Coletti, G. (2021). Decision Rules Under Vague and Uncertain Information. In: Lesot, MJ., Marsala, C. (eds) Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications. Studies in Fuzziness and Soft Computing, vol 394. Springer, Cham. https://doi.org/10.1007/978-3-030-54341-9_8

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