Abstract
AbstractThe introduction of Fuzzy Logic into Logic Programming (LP) has resulted into the development of several Fuzzy Prolog systems. These systems replace the inference mechanism of Prolog with a fuzzy variant which is able to handle partial truth. Most of these systems implement the fuzzy resolution introduced by Lee, examples being Prolog-Elf, Fril Prolog, and F-Prolog. Truth values associated to fuzzy variables can be represented in an ordeal of different flavors, such as real numbers, percentiles, intervals, unions of intervals, and continuous or discrete functions on different domains. [GMV04] presented a Fuzzy Prolog Language that models interval-valued Fuzzy Logic, implemented using CLP(\({\cal R}\)). This Fuzzy Prolog system uses both the original inference mechanism of Prolog, and constraint handling facilities provided by CLP(\({\cal R}\)) to represent and manipulate the concept of partial truth. In that approach, a truth value is a finite union of sub-intervals on [0,1]. A truth value will be propagated through the rules by means of an aggregation operator. The system is user-extensible simply by adding new aggregation operators to the library.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
