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An Online Tool for Tuning Fuzzy Logic Programs

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Rules and Reasoning (RuleML+RR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10364))

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Abstract

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.

This work has been partially supported by the EU (FEDER), the State Research Agency (AEI) and the Spanish Ministerio de Economía y Competitividad under grant TIN2016-76843-C4-2-R (AEI/FEDER, UE).

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Notes

  1. 1.

    For instance, we have typically several adjoint pairs as shown in Fig. 1: Łukasiewicz logic \( \langle \& _\mathtt {L},{\leftarrow }_\mathtt {L} \rangle \), Gödel logic \( \langle \& _\mathtt {G},{\leftarrow }_\mathtt {G} \rangle \) and product logic \( \langle \& _\mathtt {P},{\leftarrow }_\mathtt {P} \rangle \), which might be used for modeling pessimist, optimist and realistic scenarios, respectively.

  2. 2.

    A complete lattice is a (partially) ordered set \(\langle L,\preceq \rangle \) such that every subset S of L has infimum and supremum elements. It is bounded if it has bottom and top elements, denoted by \(\bot \) and \(\top \), respectively. L is said to be the carrier set of the lattice, and \(\preceq \) its ordering relation.

  3. 3.

    Here, we assume that A in \({\mathcal Q}[A]\) is the selected atom. Furthermore, as it is common practice, mgu(E) denotes the most general unifier of the set of equations E [11].

  4. 4.

    For simplicity, we consider that facts (H with v) are seen as rules of the form \((H{\leftarrow }_i \top ~with ~v)\) for some implication \({\leftarrow }_i\). Furthermore, in this case, we directly derive the state \(\langle ({\mathcal Q}[A/v])\theta ;\sigma \theta \rangle \) since for all &\(_i\).

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Authors and Affiliations

  1. Department of Computing System, University of Castilla-La Mancha, 02071, Albacete, Spain

    Ginés Moreno & José A. Riaza

Authors
  1. Ginés Moreno
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  2. José A. Riaza
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Corresponding author

Correspondence to Ginés Moreno .

Editor information

Editors and Affiliations

  1. University of L’Aquila, L’Aquila, Italy

    Stefania Costantini

  2. Free University of Bozen-Bolzano, Bolzano, Italy

    Enrico Franconi

  3. Dalhousie University, Halifax, Nova Scotia, Canada

    William Van Woensel

  4. Birkbeck, University of London, London, United Kingdom

    Roman Kontchakov

  5. Imperial College London, London, United Kingdom

    Fariba Sadri

  6. SINTEF/University of Oslo, Oslo, Norway

    Dumitru Roman

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Moreno, G., Riaza, J.A. (2017). An Online Tool for Tuning Fuzzy Logic Programs. In: Costantini, S., Franconi, E., Van Woensel, W., Kontchakov, R., Sadri, F., Roman, D. (eds) Rules and Reasoning. RuleML+RR 2017. Lecture Notes in Computer Science(), vol 10364. Springer, Cham. https://doi.org/10.1007/978-3-319-61252-2_13

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  • DOI: https://doi.org/10.1007/978-3-319-61252-2_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61251-5

  • Online ISBN: 978-3-319-61252-2

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