Abstract
This chapter deals with measure-free conditioning. It starts with the mean value based definition of conditional fuzzy subsets which again gives a fuzzy subset. Applying this general construction to indicator functions, it is proved that these conditionals form an MV-algebra and that this is isomorphic to the already known MV-algebra of the interval based conditional Boolean subsets. In the following, the problem of iteration is completely solved with the result that there are exactly two types of iteration, called the blurred resp. the sharper one, which remain in the corresponding MV-algebras. Moreover, the general concept of conditional operators plays a significant role. Finally, the problem of extending an uncertainty measure is discussed.
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Acknowledgments
I am very grateful to Peter Klement, as organizator and motor of his Linz Seminars where I received a lot of stimulations since my first participation in 1983, and as friend from our common time working together and in private occations.
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Weber, S. (2016). Conditioning for Boolean Subsets, Indicator Functions and Fuzzy Subsets. In: Saminger-Platz, S., Mesiar, R. (eds) On Logical, Algebraic, and Probabilistic Aspects of Fuzzy Set Theory. Studies in Fuzziness and Soft Computing, vol 336. Springer, Cham. https://doi.org/10.1007/978-3-319-28808-6_14
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DOI: https://doi.org/10.1007/978-3-319-28808-6_14
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