N.º 71 (2025): Enero-abril
Artículos

¿Es la lógica de Szabolcsi una lógica difusa?

PDF (English)
  • J.-Martín Castro-Manzano
J.-Martín Castro-Manzano
UPAEP
DOI: https://doi.org/10.21555/top.v710.2825

Publicado 2024-12-17

Palavras-chave

Como Citar

Castro-Manzano, J.-M. (2024). ¿Es la lógica de Szabolcsi una lógica difusa?. Tópicos, Revista De Filosofía, (71), 345–362. https://doi.org/10.21555/top.v710.2825

Direitos de Autor (c) 2024 Tópicos, Revista de Filosofía

Creative Commons License

Este trabalho encontra-se publicado com a Licença Internacional Creative Commons Atribuição-NãoComercial-SemDerivações 4.0.

Downloads

Não há dados estatísticos.

Altmetrics

Citas

Crossref
Scopus
Google Scholar
Europe PMC

Resumo

In this paper we ask ourselves whether Szabolcsi’s numerical term logic is a fuzzy logic. Our answer is in the affirmative. In order to justify such a claim, we first expound some preliminaries that help us understand why the inclusion of fuzzy quantifiers is a sufficient condition for fuzziness. Then we present Szabolcsi’s logic, which includes said quantifiers.

PDF (English)

Referências

  1. Castro-Manzano, J.-M. (2019). An Intermediate Term Functor Logic. Argumentos. Revista de Filosofia, 22, 17-31. DOI: https://doi.org/10.36517/Argumentos.22.2.
  2. Castro-Manzano, J.-M. (2021). Traditional Logic and Computational Thinking. Philosophies, 6, 12. DOI: https://doi.org/10.3390/philosophies6010012.
  3. Castro-Manzano, J.-M. (2022). On Mixing Term Logics. In B. Liao, R. Markovich, & Y. N. Wáng (eds.), Logics for New-Generation AI. Second International Workshop. 10-12 June 2021, Zhuhai. (pp. 6-23). College Publications. URL: https://www.collegepublications.co.uk/LNGAI/?00002.
  4. Correia, M. (2017). La lógica aristotélica y sus perspectivas. Pensamiento, 73(275), 5-19.
  5. Englebretsen, G. (1996). Something to Reckon with: The Logic of Terms. University of Ottawa Press.
  6. Dubois, D., Godo, L., de Màntaras, R. L., & Prade, H. (1993). Qualitative Reasoning with Imprecise Probabilities. Journal of Intelligent Information Systems, 2, 319-363. DOI: https://doi.org/10.1007/BF00961659.
  7. Dubois, D. & Prade, H. (1988). On Fuzzy Syllogisms. Computational Intelligence, 4(2), 171-179.
  8. Murphree, W. A. (1998). Numerical Term Logic. Notre Dame Journal of Formal Logic, 39, 346-362.
  9. Pereira-Fariña, M., Vidal, J. C., Díaz-Hermida, F., & Bugarín, A. (2014). A Fuzzy Syllogistic Reasoning Schema for Generalized Quantifiers. Fuzzy Sets and Systems, 234, 79-96.
  10. Peterson, P. L. (1979). On the Logic of “Few”, “Many”, and “Most”. Notre Dame Journal of Formal Logic, 20, 155-179.
  11. Simons, P. (2020). Term Logic. Axioms, 9(1), 18. DOI: https://doi.org/10.3390/axioms9010018.
  12. Sommers, F. (1982). The Logic of Natural Language. Oxford University Press.
  13. Szabolcsi, L. & Englebretsen, G. (2008). Numerical Term Logic. Edwin Mellen Press.
  14. Thompson, B. (1982). Syllogisms Using “Few”, “Many”, and “Most.” Notre Dame Journal of Formal Logic, 23, pp. 75-84.
  15. Thompson, B. (1986). Syllogisms with Statistical Quantifiers.” Notre Dame Journal of Formal Logic, 27, 93-103.
  16. Wang, P. (1997). Return to Term Logic. In P. Flach and A. Kakas (eds.), Proceedings of the IJCAI’97 Workshop on Abduction and Induction in AI. (pp. 1-9). International Joint Conferences on Artificial Intelligence Organization. URL: https://www.researchgate.net/publication/2257541_Return_to_Term_Logic.
  17. Zadeh, L. A. (1985). Syllogistic Reasoning in Fuzzy Logic and its Application to Usuality and Reasoning with Dispositions. IEEE Transactions on Systems, Man, and Cybernetics, 15(6), 754-763. DOI: https://doi.org/10.1109/TSMC.1985.6313459.