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Searching for the Unity of Science: From Classical Logic to Abductive Logical Systems

  • Ángel NepomucenoEmail author
  • Fernando Soler
  • Atocha Aliseda
Chapter
  • 568 Downloads
Part of the Logic, Epistemology, and the Unity of Science book series (LEUS, volume 18)

Abstract

From an informational point of view, an inference or argumentation can be considered as a finite sequence of sentences of a language, not arbitrarily ordered, for which one may distinguish an initial group of sentences called premises, followed by another sentence called conclusion. The set of premises (or set of reasons) may be empty, but the conclusion has to be present.

Keywords

Consequence Relation Classical Logic Operative Rule Structural Rule Negation Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Aliseda, A. (2006). Abductive Reasoning. Logical Investigations into Discovery and Explanation. Synthese Library/vol. 330. Dordrecht: Springer.Google Scholar
  2. Corcoran, J. (1999). Information-theoretic logic and transformation-theoretic logic. In Ram, M. (ed), Fragments of Science: Festschrift for Mendel Sachs, pp. 25–35. River Edge, NJ: World Scientific Publishing Co.Google Scholar
  3. Hempel, C. (1965). Aspects of Scientific Explanation and Other Essays in the Philosophy of Science. New York, NY: The Free Press.Google Scholar
  4. Hintikka, J. (1998). What is abduction? The fundamental problem of contemporary epistemology, Transactions of the Charles S. Peirce Society, 34(3), 503–533.Google Scholar
  5. Kakas, A., Kowalski, R., Toni, F. (1998). The role of abduction in logic programming. In Handbook of Logic in Artificial Intelligence and Logic Programming, pp. 235–324. Oxford: Oxford University Press.Google Scholar
  6. Konolige, K. (1996). Abductive theories in artificial intelligence. In Brewka, G. (ed), Principles of Knowledge Representation, pp. 129–152. Stanford, CA: CSLI Publications.Google Scholar
  7. Lobo, J., Uzcategui, C. (1997). Abductive consequence relations, Artificial Intelligence, 89, 149–171.CrossRefGoogle Scholar
  8. Makinson, D. (2005). Bridges from Classical to Nonmonotonic Logic. London: King’s College.Google Scholar
  9. Mayer, M. C., Pirri, F. (1993). First order abduction via tableau and sequent calculi, Bulletin of the IGPL 1, 99–117.CrossRefGoogle Scholar
  10. Nepomuceno, A. (2002). Scientific explanation and modified semantic tableaux. In Magnani, L., Nerssessian, N., Pizzi C. (eds), Logical and Computational Aspects of Model-Based Reasoning, pp. 181–198. Applied Logic Series. Dordrecht: Kluwer Academic Publishers.Google Scholar
  11. Nepomuceno, A. (2007). Information and logic. In Proceedings of Symposium in Honour of John Corcoran. Spain: Universidad de Santiago de Compostela.Google Scholar
  12. Peirce, C. S. (1931–1935). Collected Papers of Charles Sanders Peirce, 1–6 vols. In Hartshorne, C., Weiss, P. (eds), Cambridge: Harvard University Press; and vols. 7–8, edited by A. W. Burks, Cambridge, Harvard University Press.Google Scholar
  13. Schroeder-Heister, P., Dośen, K. (eds), (1999). Substructural Logics. Oxford: Oxford Science Publications.Google Scholar
  14. Soler-Toscano, F., Nepomuceno-Fernández, A., Aliseda-Llera, A. (2006). Model based abduction via dual resolution, Logic Journal of the IGPL 14(2), 305–319.CrossRefGoogle Scholar
  15. Thagard, P. (1988). Computational Philosophy of Science. Cambridge, MA: The MIT Press.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Ángel Nepomuceno
    • 1
    Email author
  • Fernando Soler
    • 1
  • Atocha Aliseda
    • 2
  1. 1.Department of Philosophy, Logic and Philosophy of ScienceUniversity of SevilleSevilleSpain
  2. 2.Instituto de Investigaciones Filosóficas, U. N. A. M.MexicoMexico

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