Programming with Fuzzy Logic Rules by Using the FLOPER Tool

Morcillo, Pedro J.; Moreno, Ginés

doi:10.1007/978-3-540-88808-6_14

Cited by 26 publications

(7 citation statements)

References 7 publications

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“…They are used to build the framework of multi-adjoint logic programming in [11,26], but the relevant fact is the relation between adjoint pairs ( i , & i ), which makes it possible to evaluate in the manyvalued modus ponens the truth value of the head of a rule from the truth value of the body and the weight of the rule: ðB; zÞ; ðB ! A; xÞ ðA; yÞ ;…”

Section: About Multi-adjoint Logic Programmingmentioning

confidence: 99%

RFuzzy: Syntax, semantics and implementation details of a simple and expressive fuzzy tool over Prolog

Muñoz-Hernández

Pablos-Ceruelo

Straß

2011

Information Sciences

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Section: About Multi-adjoint Logic Programmingmentioning

confidence: 99%

RFuzzy: Syntax, semantics and implementation details of a simple and expressive fuzzy tool over Prolog

Muñoz-Hernández

Pablos-Ceruelo

Straß

2011

Information Sciences

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“…(ii) Regarding implementation issues, our efforts are devoted to incorporate the proposed technique inside the kernel of the FLOPER environment (see [21] and visit http://www.dsi.uclm.es/investigacion/dect/FLOPERpage.htm).…”

Section: Conclusion and Further Researchmentioning

confidence: 99%

Thresholded Tabulation in a Fuzzy Logic Setting

Julián

Medina

Moreno

et al. 2009

Electronic Notes in Theoretical Computer Science

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Fuzzy logic programming represents a flexible and powerful declarative paradigm amalgamating fuzzy logic and logic programming, for which there exists different promising approaches described in the literature. In this paper we propose an improved fuzzy query answering procedure for the so called multi-adjoint logic programming approach, which avoids the re-evaluation of goals and the generation of useless computations thanks to the combined use of tabulation with thresholding techniques. The general idea is that, when trying to perform a computation step by using a given program rule R, we firstly analyze if such step might contribute to reach further significant solutions (non tabulated yet). When it is the case, it is possible to avoid a useless computation step via a rule R by using thresholds and filters based on the truth degree of R, as well as a safe, accurate and dynamic estimation of the maximum truth degree associated to its body.

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“…As shown in the web page http://dectau.uclm.es/floper/ designed in our research group for freely accessing  -see also references [20]- [25]-during the last years we have been involved in the development of this tool for aliving MALP programs (which can be easily loaded into the system by means of plain-text files with extension ".fpl"). For example, our previous illustrative program included into file "P1.fpl", contains the following rules where, note for instance that the fuzzy connectives for implication, disjunction and conjunction symbols belonging to the product logic are respectively referred as "<prod", "|prod" and "&prod":…”

Section: The "Fuzzy Logic Programming Environment For Research" mentioning

confidence: 99%

Fuzzy Logic Programming in Action with <i>FLOPER</i>

Moreno¹,

Vázquez²

2014

JSEA

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During the last years, we have developed the  platform for providing a practical support to the so-called Multi-Adjoint Logic Programming approach (MALP in brief), which represents an extremely flexible framework into the Fuzzy Logic Programming arena. Nowadays,  is useful for compiling (to standard Prolog code), executing and debugging (by drawing execution trees) MALP programs, and it is ready for being extended in the near future with powerful transformation and optimization techniques designed in our research group during the recent past. Our last update consists in the integration of a graphical interface for a comfortable interaction with the system which allows, among other capabilities, the use of projects for packing scripts and auxiliary definitions of fuzzy sets/connectives, together with fuzzy programs and their associated lattices modeling truth-degrees beyond the simpler crisp case { ; } true false .

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Programming with Fuzzy Logic Rules by Using the FLOPER Tool

Cited by 26 publications

References 7 publications

RFuzzy: Syntax, semantics and implementation details of a simple and expressive fuzzy tool over Prolog

RFuzzy: Syntax, semantics and implementation details of a simple and expressive fuzzy tool over Prolog

Thresholded Tabulation in a Fuzzy Logic Setting

Fuzzy Logic Programming in Action with <i>FLOPER</i>

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Programming with Fuzzy Logic Rules by Using the FLOPER Tool

Cited by 26 publications

References 7 publications

RFuzzy: Syntax, semantics and implementation details of a simple and expressive fuzzy tool over Prolog

RFuzzy: Syntax, semantics and implementation details of a simple and expressive fuzzy tool over Prolog

Thresholded Tabulation in a Fuzzy Logic Setting

Fuzzy Logic Programming in Action with &lt;i&gt;FLOPER&lt;/i&gt;

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Product

Resources

About

Fuzzy Logic Programming in Action with <i>FLOPER</i>