PhD student of Computer Science at UCLM. Researching on Fuzzy Logic Programming and Automatic Program Transformation.
I am a member of the Declarative Programming and Automatic Program Transformation group (DEC-Tau) at the Albacete Research Institute for Informatics (I3A) in the University of Castilla-La Mancha.
My research is focused on Declarative Programming, concretely in the field of Fuzzy Logic Programming and Automatic Program Transformation.
The unfolding transformation has been widely used in many declarative frameworks for improving the efficiency of programs after applying computational steps on their rules. In this paper we apply such operation to a symbolic extension of a modern fuzzy logic language where program rules extend the classical notion of clause by adding concrete and/or symbolic fuzzy connectives and truth degrees on their bodies.
A few years ago, the LatticeMaker tool was born in our research group for aiding the graphical design of lattices of truth degrees and generating code in form of Prolog clauses which can be directly imported by the fuzzy logic programming environment FLOPER built too by our team. In this work we extend the capabilities of LatticeMaker by focusing on testing properties related to fuzzy connectives and distance measures, being these actions also connected with advanced techniques (nowadays under implementation on the FLOPER platform) for unfolding and tuning fuzzy logic programs.
The unfolding transformation has been widely used in many declarative frameworks for improving the efficiency and scalability of programs after applying computational steps on their rules. Inspired by our previous experiences in fuzzy logic languages not dealing with similarity relations, in this work we adapt such operation to the so-called FASILL language (acronym of <
Fuzzy logic programming is a growing declarative paradigm aiming to integrate fuzzy logic into logic programming. One of the most difficult tasks when specifying a fuzzy logic program is determining the right weights for each rule, as well as the most appropriate fuzzy connectives and operators. In this paper, we introduce a symbolic extension of fuzzy logic programs in which some of these parameters can be left unknown, so that the user can easily see the impact of their possible values. Furthermore, given a number of test cases, the most appropriate values for these parameters can be automatically computed. Finally, we show some benchmarks that illustrate the usefulness of our approach.
In this paper we are concerned with a fuzzy logic language where program rules extend the classical notion of clause by adding fuzzy connectives and truth degrees on their bodies. In this work we describe an efficient online tool which helps to select such operators and weights in an automatic way, accomplishing with our recent technique for tuning this kind of fuzzy programs. The system offers a comfortable interaction with users for introducing test cases and also provides useful information about the choices that better fit their preferences.
José Antonio Riaza Valverde