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Fuzzy Positive Primitive Formulas

  • Pilar Dellunde
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11144)

Abstract

Can non-classical logic contribute to the analysis of complexity in computer science? In this paper, we give a step towards the solution of this open problem, taking a logical model-theoretic approach to the analysis of complexity in fuzzy constraint satisfaction. We study fuzzy positive-primitive sentences, and we present an algebraic characterization of classes axiomatized by this kind of sentences in terms of homomorphisms and finite direct products. The ultimate goal is to study the expressiveness and reasoning mechanisms of non-classical languages, with respect to constraint satisfaction problems and, in general, in modelling decision scenarios.

Keywords

Fuzzy constraint satisfaction Preference modeling Fuzzy logics Model theory 

Notes

Acknowledgements

The research leading to these results has received funding from RecerCaixa. This project has also received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 689176 (SYSMICS project), and by the projects RASO TIN2015-71799-C2-1-P, CIMBVAL TIN2017-89758-R, and the grant 2017SGR-172 from the Generalitat de Catalunya. The author would like to thank the reviewers for their comments, and the Algorithmic Decision Theory Group of Data61 (UNSW, Sydney) for hosting me during this research.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Universitat Autònoma de BarcelonaBarcelonaSpain
  2. 2.Barcelona Graduate School of MathematicsBarcelonaSpain
  3. 3.Artificial Intelligence Research Institute IIIA-CSICBarcelonaSpain

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