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Convex MV-Algebras: Many-Valued Logics Meet Decision Theory

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This paper introduces a logical analysis of convex combinations within the framework of Łukasiewicz real-valued logic. This provides a natural link between the fields of many-valued logics and decision theory under uncertainty, where the notion of convexity plays a central role. We set out to explore such a link by defining convex operators on MV-algebras, which are the equivalent algebraic semantics of Łukasiewicz logic. This gives us a formal language to reason about the expected value of bounded random variables. As an illustration of the applicability of our framework we present a logical version of the Anscombe–Aumann representation result.

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Flaminio, T., Hosni, H. & Lapenta, S. Convex MV-Algebras: Many-Valued Logics Meet Decision Theory. Stud Logica 106, 913–945 (2018).

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