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Heterogeneous Approximate Reasoning with Graded Truth Values

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Rough Sets (IJCRS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10313))

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Abstract

This paper is devoted to paraconsistent approximate reasoning with graded truth-values. In the previous research we introduced a family of many-valued logics parameterized by a variable number of truth/falsity grades together with a corresponding family of rule languages with tractable query evaluation. Such grades are shown here to be a natural qualitative counterpart of quantitative measures used in various forms of approximate reasoning. The developed methodology allows one to obtain a framework unifying heterogeneous reasoning techniques, providing also the logical machinery to resolve partial and incoherent information that may arise after unification. Finally, we show the introduced framework in action, emphasizing its expressiveness in handling heterogeneous approximate reasoning in realistic scenarios.

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Notes

  1. 1.

    Note that, in the classical setting, \(R^+(a)+R^-(a)=1\). If, however, the values of A(z) may be unknown or inconsistent then these values do not have to sum up to 1.

  2. 2.

    Of course, one could also adapt here the method for fuzzy sets provided in Sect. 3.1.

  3. 3.

    A video of the prototype is available at:https://www.youtube.com/watch?v=4u_O6-ylhvU.

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Acknowledgments

The last two authors have been supported by the Polish National Science Centre grant 2015/19/B/ST6/02589.

Author information

Authors and Affiliations

  1. Institute of Services Science, University of Geneva, 1227, Carouge, Switzerland

    Francesco Luca De Angelis & Giovanna Di Marzo Serugendo

  2. Institute of Informatics, University of Warsaw, ul. Banacha 2, 02-097, Warsaw, Poland

    Barbara Dunin-Kęplicz & Andrzej Szałas

  3. Department of Computer and Information Science, Linköping University, 581 83, Linköping, Sweden

    Andrzej Szałas

Authors
  1. Francesco Luca De Angelis
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  2. Giovanna Di Marzo Serugendo
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  3. Barbara Dunin-Kęplicz
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  4. Andrzej Szałas
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Corresponding author

Correspondence to Andrzej Szałas .

Editor information

Editors and Affiliations

  1. Polish-Japanese Academy of Information Technology, Warsaw, Poland

    Lech Polkowski

  2. University of Regina, Regina, SK, Canada

    Yiyu Yao

  3. University of Warmia and Mazury, Olsztyn, Poland

    Piotr Artiemjew

  4. University of Milano-Bicocca, Milano, Italy

    Davide Ciucci

  5. Southwest Jiaotong University, Chengdu, China

    Dun Liu

  6. Warsaw University, Warszawa, Poland

    Dominik Ślęzak

  7. Silesian University, Sosnowiec, Poland

    Beata Zielosko

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De Angelis, F.L., Di Marzo Serugendo, G., Dunin-Kęplicz, B., Szałas, A. (2017). Heterogeneous Approximate Reasoning with Graded Truth Values. In: Polkowski, L., et al. Rough Sets. IJCRS 2017. Lecture Notes in Computer Science(), vol 10313. Springer, Cham. https://doi.org/10.1007/978-3-319-60837-2_6

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  • DOI: https://doi.org/10.1007/978-3-319-60837-2_6

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