A Fuzzy Logic Programming Environment for Managing Similarity and Truth Degrees

FASILL (acronym of "Fuzzy Aggregators and Similarity Into a Logic Language") is a fuzzy logic programming language with implicit/explicit truth degree annotations, a great variety of connectives and unification by similarity. FASILL integrates and extends features coming from MALP (Multi-Adjoint Logic Programming, a fuzzy logic language with explicitly annotated rules) and Bousi~Prolog (which uses a weak unification algorithm and is well suited for flexible query answering). Hence, it properly manages similarity and truth degrees in a single framework combining the expressive benefits of both languages. This paper presents the main features and implementations details of FASILL. Along the paper we describe its syntax and operational semantics and we give clues of the implementation of the lattice module and the similarity module, two of the main building blocks of the new programming environment which enriches the FLOPER system developed in our research group.Comment: In Proceedings PROLE 2014, arXiv:1501.0169

String-based Multi-adjoint Lattices for Tracing Fuzzy Logic Computations

Classically, most programming languages use in a predefined way thenotion of “string” as an standard data structure for a comfortable management of arbitrary sequences of characters. However, in this paper we assign a different role to this concept: here we are concerned with fuzzy logic programming, a somehow recent paradigm trying to introduce fuzzy logic into logic programming. In this setting, the mathematical concept of multi-adjoint lattice has been successfully exploited into the so-called Multi-adjoint Logic Programming approach, MALP in brief, for modeling flexible notions of truth-degrees beyond the simpler case of true and false. Our main goal points out not only our formal proof verifying that stringbased lattices accomplish with the so-called multi-adjoint property (as well as its Cartesian product with similar structures), but also its correspondence with interesting debugging tasks into the FLOPER system (from “Fuzzy LOgic Programming Environment for Research”) developed in our research group

Automatic Proving of Fuzzy Formulae with Fuzzy Logic Programming and SMT

In this paper we deal with propositional fuzzy formulae containing severalpropositional symbols linked with connectives defined in a lattice of truth degrees more complex than Bool. We firstly recall an SMT (Satisfiability Modulo Theories) based method for automatically proving theorems in relevant infinitely valued (including Łukasiewicz and G¨odel) logics. Next, instead of focusing on satisfiability (i.e., proving the existence of at least one model) or unsatisfiability, our interest moves to the problem of finding the whole set of models (with a finite domain) for a given fuzzy formula. We propose an alternative method based on fuzzy logic programming where the formula is conceived as a goal whose derivation tree contains on its leaves all the models of the original formula, by exhaustively interpreting each propositional symbol in all the possible forms according the whole setof values collected on the underlying lattice of truth-degrees

Analyzing Fuzzy Logic Computations with Fuzzy XPath

Implemented with a fuzzy logic language by using the FLOPER tool developed in our research group, we have recently designed a fuzzy dialect of the popular XPath language for the flexible manipulation of XML documents. In this paper we focus on the ability of Fuzzy XPath for exploring derivation trees generated by FLOPER once they are exported in XML format, which somehow serves as a debugging/analizing tool for discovering the set of fuzzy computed answers for a given goal, performing depth/breadth-first traversals of its associated derivation tree, finding non fully evaluated branches, etc., thus reinforcing the bi-lateral synergies between Fuzzy XPath and FLOPER

A Survey of Fuzzy Systems Software: Taxonomy, Current Research Trends, and Prospects

Fuzzy systems have been used widely thanks to their ability to successfully solve a wide range of problems in different application fields. However, their replication and application require a high level of knowledge and experience. Furthermore, few researchers publish the software and/or source code associated with their proposals, which is a major obstacle to scientific progress in other disciplines and in industry. In recent years, most fuzzy system software has been developed in order to facilitate the use of fuzzy systems. Some software is commercially distributed, but most software is available as free and open-source software, reducing such obstacles and providing many advantages: quicker detection of errors, innovative applications, faster adoption of fuzzy systems, etc. In this paper, we present an overview of freely available and open-source fuzzy systems software in order to provide a well-established framework that helps researchers to find existing proposals easily and to develop well-founded future work. To accomplish this, we propose a two-level taxonomy, and we describe the main contributions related to each field. Moreover, we provide a snapshot of the status of the publications in this field according to the ISI Web of Knowledge. Finally, some considerations regarding recent trends and potential research directions are presentedThis work was supported in part by the Spanish Ministry of Economy and Competitiveness under Grants TIN2014-56633-C3-3-R and TIN2014-57251-P, the Andalusian Government under Grants P10-TIC-6858 and P11-TIC-7765, and the GENIL program of the CEI BioTIC GRANADA under Grant PYR-2014-2S

Farmer's Mail & Breeze, v. 46, no. 7 (February 12, 1916)

Published as: Kansas Farmer, Vol. 1, no. 1 (May 1, 1863)-v. 57, no. 49 (Dec. 6, 1919); Kansas Farmer and Mail & Breeze, Vol. 57, no. 50 (Dec 13, 1919)-v. 64, no. 9 (Feb 27, 1926); Kansas Farmer, Mail & Breeze, Vol. 64, no. 10 (Mar. 6, 1926)-v. 70, no. 1 (Jan. 9, 1932); Kansas Farmer Continuing Mail & Breeze, Vol. 70, no. 2 (Jan. 23, 1932)-v. 76, no. 8 (Apr. 22, 1939); Kansas Farmer, Mail & Breeze, Vol. 76, no. 9 (May 6, 1939)-v. 77, no. 20 (Oct. 5, 1940); Kansas Farmer Continuing Mail & Breeze, Vol. 77, no. 21 (Oct. 19, 1940)-v. 91, no. 3 (Feb. 6, 1954).Issued by Kansas Farmer Co., 1863-1919; Kansas Farmer and Mail & Breeze, 1919-1926; Kansas Farmer, 1926-1954.Missing issues and volumes arranged chronologically by date and journal name: Kansas Farmer: vol. 6, nos. 2-8, 10 and 12 (1869); vol. 9, no. 10 (1872); vol. 14, no. 50 (1876); vol. 18, nos. 1, 12 and 13 (1880); vol. 24. no. 16 (1886); vol. 35 (1897); vol. 38 (1900); vol. 41, nos. 52 and 53 (1903); vol. 42, nos. 17 and 35 (1904); vol. 48, nos. 11 and 53 (1910); vol. 50, nos. 45-50 (1912); vol. 53 (1915); vol. 56 (1918); vol. 49, no. 39 (1919); Kansas Farmer, Continuing Mail & Breeze: vol. 73 (1935); vol. 85, nos. 9-17 (1948); and The Farmers Mail and Breeze: vol. 49, no. 39 (1919).Call number: S544.3.K3 K3