Abstract
A powerful research line in the design of declarative languages consists in the introduction of expressive resources with a fuzzy taste on their cores, in order to provide comfortable computational constructs for easily solving real-world scientific/engineering problems. Into the fuzzy logic programming arena, the so-called multi-adjoint approach (MALP in brief) has emerged as an interesting paradigm for which our research group has developed during the last years the \(\mathcal F \mathcal L \mathcal O \mathcal P \mathcal E \mathcal R\) programming environment and the FuzzyXPath application in the field of the semantic web. Since the practicality of declarative languages is strongly dependent of their theoretical foundations, here we focus on topics related with the declarative semantics of the MALP framework. So, under an innovative point of view relying on fuzzy sets theory, in this paper we re-formulate in a very simple and elegant way our original model theory-based notions of least fuzzy Herbrand model and (fuzzy) correct answer. Apart for simplifying the proofs relating these concepts, our results are nicely strengthened with homologous ones in the field of pure logic programming, but largely surpassing them thanks to the fuzzy dimension of the MALP language.
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Moreno, G., Penabad, J., Vázquez, C. (2014). Fuzzy Sets for a Declarative Description of Multi-adjoint Logic Programming. In: Cornelis, C., Kryszkiewicz, M., Ślȩzak, D., Ruiz, E.M., Bello, R., Shang, L. (eds) Rough Sets and Current Trends in Computing. RSCTC 2014. Lecture Notes in Computer Science(), vol 8536. Springer, Cham. https://doi.org/10.1007/978-3-319-08644-6_7
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DOI: https://doi.org/10.1007/978-3-319-08644-6_7
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