Fuzzy Positive Primitive Formulas

Pilar Dellunde*

*Corresponding author for this work

Research output: Chapter in BookChapterResearchpeer-review

1 Citation (Scopus)


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.

Original languageEnglish
Title of host publicationModeling Decisions for Artificial Intelligence - 15th International Conference, MDAI 2018, Proceedings
EditorsVicenc Torra, Vicenc Torra, Yasuo Narukawa, Manuel González-Hidalgo, Isabel Aguilo
Number of pages13
Publication statusPublished - 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11144 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


  • Fuzzy constraint satisfaction
  • Fuzzy logics
  • Model theory
  • Preference modeling


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