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European Workshop on Logics in Artificial Intelligence

JELIA 2014: Logics in Artificial Intelligence pp 326–339Cite as

Stable Models of Fuzzy Propositional Formulas

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8761))

Abstract

We introduce the stable model semantics for fuzzy propositional formulas, which generalizes both fuzzy propositional logic and the stable model semantics of Boolean propositional formulas. Combining the advantages of both formalisms, the introduced language allows highly configurable default reasoning involving fuzzy truth values. We show that several properties of Boolean stable models are naturally extended to this formalism, and discuss how it is related to other approaches to combining fuzzy logic and the stable model semantics.

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Author information

Authors and Affiliations

  1. School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, USA

    Joohyung Lee & Yi Wang

Authors
  1. Joohyung Lee
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  2. Yi Wang
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Editor information

Editors and Affiliations

  1. University of Madeira, Funchal, Madeira, Portugal

    Eduardo Fermé

  2. CENTRIA, Universidade Nova de Lisboa, Caparica, Portugal

    João Leite

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Lee, J., Wang, Y. (2014). Stable Models of Fuzzy Propositional Formulas. In: Fermé, E., Leite, J. (eds) Logics in Artificial Intelligence. JELIA 2014. Lecture Notes in Computer Science(), vol 8761. Springer, Cham. https://doi.org/10.1007/978-3-319-11558-0_23

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  • DOI: https://doi.org/10.1007/978-3-319-11558-0_23

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11557-3

  • Online ISBN: 978-3-319-11558-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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