Extending Prolog with Incomplete Fuzzy Information

Extending Prolog with Incomplete Fuzzy Information. Susana Munoz-Hernandez, Claudio Vaucheret. 2005.

Our first work (Fuzzy Prolog) was a language that models $\mathcal{B}([0,1])$-valued Fuzzy Logic. In the Borel algebra, $\mathcal{B}([0,1])$, truth value is represented using unions of intervals of real numbers. This work was more general in truth value representation and propagation than previous works.
An interpreter for this language using Constraint Logic Programming over Real numbers (CLP(${\cal R}$)) was implemented and is available in the Ciao system. Now, we enhance our former approach by using default knowledge to represent incomplete information in Logic Programming. We also provide the implementation of this new framework. This new release of Fuzzy Prolog handles incomplete information, it has a complete semantics (the previous one was incomplete as Prolog) and moreover it is able to combine crisp and fuzzy logic in Prolog programs.

A project of related interest is Fril which as far as I remember wasn't discussed here.

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Maybe?

So, if the answer to any prolog program is "No.", is the answer here "Maybe."?

Maybe. Maybe not.

Maybe. Maybe not.