Academia.eduAcademia.edu

Outline

Minimal inconsistency-tolerant logics: a quantitative approach

2025, Australasian Journal of Logic

Abstract

In order to reason in a non-trivializing way with contradictions, paraconsistent logics reject some classically valid inferences. As a way of recovering some of these inferences, Graham Priest (Priest (1991)) proposed to nonmonotonically strengthen the Logic of Paradox by allowing the selection of "less inconsistent" models via a comparison of their respective inconsistent parts. This move recaptures a good portion of classical logic in that it does not block, e.g., disjunctive syllogism, unless it is applied to contradictory assumptions. In Priest's approach the inconsistent parts of models are compared in an extensional way by considering their inconsistent objects. This distinguishes his system from the standard format of (inconsistency-)adaptive logics pioneered by Diderik Batens, according to which (atomic) contradictions validated in models form the basis of their comparison. A well-known problem for Priest's extensional approach is its lack of the Strong Reassurance property, i.e., for specific settings there may be infinitely descending chains of less and less inconsistent models, thus never reaching a minimally inconsistent model. In this paper, we demonstrate that Strong Reassurance holds for the extensional approach under a cardinality-based comparison of the inconsistent parts of models. Furthermore, we introduce and investigate the metatheory of the class of first-order nonmonotonic inconsistencytolerant construct over the extensional or quantitative comparisons of their respective models. Core model-theoretic properties for these logics, such as the Löwenheim-Skolem theorems, along with other nonmonotonic properties, are further studied.

References (29)

  1. Asenjo, F. G., et al. (1966). A calculus of antinomies. Notre Dame Journal of Formal Logic, 7 (1), 103-105.
  2. Avron, A. (2005). A non-deterministic view on non-classical negations. Studia Logica, 80 (2-3), 159-194.
  3. Avron, A., & Zamansky, A. (2005). Quantification in non-deterministic multi-valued structures. In 35th International Symposium on Multiple-Valued Logic (ISMVL'05), (pp. 296-301). IEEE.
  4. Batens, D. (1999). Linguistic and ontological measures for comparing the inconsistent parts of models. Logique et Analyse, (pp. 5-33).
  5. Batens, D. (2000). Minimally abnormal models in some adaptive logics. Synthese, 125 (1-2), 5-18.
  6. Batens, D. (2007). A universal logic approach to adaptive logics. Logica universalis, 1 (1), 221-242.
  7. Crabbé, M. (2011). Reassurance for the logic of paradox. The Review of Symbolic Logic, 4 (03), 479-485.
  8. Ferguson, T. M. (2014). On non-deterministic quantification. Logica Universalis, 8 (2), 165-191.
  9. Ferguson, T. M. (2020). Variations on the collapsing lemma. In Graham Priest on Dialetheism and Paraconsistency, (pp. 249-270). Springer.
  10. Gabbay, D. M. (1985). Theoretical foundations for non-monotonic reasoning in expert systems. In Logics and models of concurrent systems, (pp. 439-457). Springer.
  11. Horty, J. F. (1994). Some direct theories of nonmonotonic inheritance. Handbook of logic in artificial intelligence and logic programming, 3 , 111-187.
  12. Kraus, S., Lehmann, D., & Magidor, M. (1990). Nonmonotonic reasoning, preferential models and cumulative logics. Artificial intelligence, 44 (1-2), 167-207.
  13. Lehmann, D., & Magidor, M. (1992). What does a conditional knowledge base entail? Artificial intelligence, 55 (1), 1-60.
  14. Makinson, D. (2005). Bridges from classical to nonmonotonic logic, volume 5 of texts in computing. king's college publications. London, UK .
  15. Makinson, D., & Van Der Torre, L. (2000). Input/output logics. Journal of Philosophical Logic, 29 (4), 383-408.
  16. Meheus, J., Straßer, C., & Verdée, P. (2013). Which style of reasoning to choose in the face of conflicting information? Journal of logic and Computation, 26 (1), 361-380.
  17. Omori, H., & Wansing, H. (2017). 40 years of FDE: an introductory overview. Studia Logica, 105 (6), 1021-1049. URL http://dx.doi.org/10.1007/s11225-017-9748-6
  18. Priest, G. (1979). The logic of paradox. Journal of Philosophical logic, 8 (1), 219-241.
  19. Priest, G. (1988). Consistency by default. Technical Report Reasoning Project, Australian National University.
  20. Priest, G. (1991). Minimally inconsistent LP. Studia Logica, 50 (2), 321-331.
  21. Priest, G. (2002). Paraconsistent logic. In Handbook of philosophical logic, (pp. 287-393). Springer.
  22. Priest, G. (2014). One: Being an Investigation into the Unity of Reality and of its Parts, including the Singular Object which is Nothingness. Oxford University Press.
  23. Priest, G. (2017). What if? the exploration of an idea. The Australasian Journal of Logic, 14 (1).
  24. Priest, G., Tanaka, K., & Weber, Z. (2018). Paraconsistent Logic. In E. N. Zalta (Ed.) The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University, summer 2018 ed.
  25. Reiter, R. (1980). A logic for default reasoning. Artificial intelligence, 13 (1-2), 81-132.
  26. Rott, H. (2017). Stability and scepticism in the modelling of doxastic states: Probabilities and plain beliefs. Minds and Machines, 27 (1), 167-197.
  27. Šešelja, D., & Straßer, C. (2014). Concerning Peter Vickers's recent treatment of 'paraconsistencitis'. International Studies in the Philosophy of Science, 28 (3), 325-340.
  28. Straßer, C. (2014). Adaptive logics for defeasible reasoning. Springer.
  29. Vickers, P. (2013). Understanding inconsistent science. OUP Oxford.