Mathematical Fuzzy Logic in Reasoning and Decision Making under Uncertainty

Here’s the abstract of my forthcoming talk at the Prague Seminar: The Future of Mathematical Fuzzy Logic Prague, 16–18. June 2016

Mathematical Fuzzy Logic in Reasoning and Decision Making under Uncertainty

“Fuzzy methods” are currently ubiquitous in many economic applications, especially to business and marketing. In philosophy “fuzzy logic” has long been discussed in connection with vagueness and its linguistic consequences. Both areas have played an important role and ultimately brought about a number of contributions envisaged by the early works in “fuzzy sets”. Over the past two decades, much work has been done to connect the early contributions to the wider logical landscape, resulting in what has been eventually termed Mathematical Fuzzy Logic. As a branch of mathematical logic, MFL developed its own tools and methods which partly advanced our understanding of many-valued logics, and partly lead to new logical systems. I will begin by pointing out two examples of how MFL helps us framing the discussion on central concepts in philosophy, (graded truth) and decision theory (convexity). Building on those, I will then suggest that a number of foundational problems in the social sciences lend themselves to being tackled from the MFL perspective (rather from the “fuzzy methods” perspectives.) The question then becomes: How does MFL help us rethink the foundations of reasoning and decision-making under uncertainty?

 

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