Stable models of fuzzy propositional formulas

Joohyung Lee, Yi Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We introduce the stable model semantics for fuzzy propositional formulas, which generalizes both fuzzy propositional logic and the stable model semantics of classical 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.

Original languageEnglish (US)
Title of host publicationCEUR Workshop Proceedings
PublisherCEUR-WS
Pages114-126
Number of pages13
Volume1205
StatePublished - 2014
Event1st Workshop on Logics for Reasoning About Preferences, Uncertainty, and Vagueness, PRUV 2014 - Vienna, Austria
Duration: Jul 23 2014Jul 24 2014

Other

Other1st Workshop on Logics for Reasoning About Preferences, Uncertainty, and Vagueness, PRUV 2014
CountryAustria
CityVienna
Period7/23/147/24/14

    Fingerprint

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Lee, J., & Wang, Y. (2014). Stable models of fuzzy propositional formulas. In CEUR Workshop Proceedings (Vol. 1205, pp. 114-126). CEUR-WS.