Abstract
This paper includes the main notions associated with the syntax and semantics of two interesting paradigms in fuzzy logic programming with default negation: multi-adjoint normal logic programming introduced in [5] and the fuzzy answer set logic programming approach presented in [16]. We will show that fuzzy answer set logic programs can be translated into multi-adjoint normal logic programs, as long as the implication operator used in the former is a residuated implication. Moreover, we will relate the notions of fuzzy y-model and model by means of a characterization theorem which allow us to guarantee the existence of fuzzy y-models of fuzzy answer set logic programs.
Partially supported by the State Research Agency (AEI) and the European Regional Development Fund (ERDF) project TIN2016-76653-P, and by the research and transfer program of the University of Cádiz.
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Cornejo, M.E., Lobo, D., Medina, J. (2018). Characterizing Fuzzy y-Models in Multi-adjoint Normal Logic Programming. In: Medina, J., Ojeda-Aciego, M., Verdegay, J., Perfilieva, I., Bouchon-Meunier, B., Yager, R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications. IPMU 2018. Communications in Computer and Information Science, vol 855. Springer, Cham. https://doi.org/10.1007/978-3-319-91479-4_45
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