Rfuzzy framework

TL;DR

Rfuzzy is a modern, user-friendly framework for fuzzy reasoning that models multi-adjoint logic, offering extensions like default values and typed variables for easier problem representation and interpretation.

Contribution

It introduces Rfuzzy, a new framework that simplifies fuzzy reasoning by integrating multi-adjoint logic with practical extensions and straightforward query results.

Findings

Rfuzzy effectively models multi-adjoint logic.

It simplifies fuzzy reasoning for users.

Provides direct query results instead of constraints.

Abstract

Fuzzy reasoning is a very productive research field that during the last years has provided a number of theoretical approaches and practical implementation prototypes. Nevertheless, the classical implementations, like Fril, are not adapted to the latest formal approaches, like multi-adjoint logic semantics. Some promising implementations, like Fuzzy Prolog, are so general that the regular user/programmer does not feel comfortable because either representation of fuzzy concepts is complex or the results difficult to interpret. In this paper we present a modern framework, Rfuzzy, that is modelling multi-adjoint logic. It provides some extensions as default values (to represent missing information, even partial default values) and typed variables. Rfuzzy represents the truth value of predicates through facts, rules and functions. Rfuzzy answers queries with direct results (instead of constraints) and it is easy to use for any person that wants to represent a problem using fuzzy reasoning in a simple way (by using the classical representation with real numbers).