Foundations of Science

, Volume 16, Issue 1, pp 47–65

Defeasible Reasoning + Partial Models: A Formal Framework for the Methodology of Research Programs



In this paper we show that any reasoning process in which conclusions can be both fallible and corrigible can be formalized in terms of two approaches: (i) syntactically, with the use of defeasible reasoning, according to which reasoning consists in the construction and assessment of arguments for and against a given claim, and (ii) semantically, with the use of partial structures, which allow for the representation of less than conclusive information. We are particularly interested in the formalization of scientific reasoning, along the lines traced by Lakatos’ methodology of scientific research programs. We show how current debates in cosmology could be put into this framework, shedding light on a very controversial topic.


Partial structures Defeasible reasoning Lakatos Cosmology 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Arp, H. and more than other 30 signatures (2004). An open letter to the scientific community. New Scientist 2448, May 22 (also in
  2. Bueno O., de Souza E. (1996) The concept of quasi-truth. Logique et Analyse 153(154): 183–189Google Scholar
  3. Castelvecchi, D. (2004). The growth of inflation. Symmetry ( 01(2)
  4. Coles P., Lucchin F. (1995) Cosmology: The origin and evolution of cosmic structure. John Wiley, NYGoogle Scholar
  5. da Costa N. C. A., French S. (1989) Pragmatic truth and the logic of induction. British Journal of Philosophy of Science 40: 333–356CrossRefGoogle Scholar
  6. da Costa N. C. A., French S. (1990) The model-theoretic approach in the philosophy of science. Philosophy of Science 57: 248–265CrossRefGoogle Scholar
  7. da Costa N. C. A., Bueno O., French S. (1998) The logic of pragmatic truth. Journal of Philosophical Logic 27: 603–620CrossRefGoogle Scholar
  8. Delrieux, C. (2001). The role of defeasible reasoning in the modelling of scientific research programmes. Proceedings of the first international workshop on computer modeling of scientific reasoning and applications (pp. 861–869), Las Vegas (Nevada).Google Scholar
  9. Dung P. (1995) On the acceptability of arguments and its fundamental role in non-monotonic reasoning, logic programming and n-person games. Artificial Intelligence 77: 331–357CrossRefGoogle Scholar
  10. Earman J., Mosterin J. (1999) A critical look at inflationary cosmology. Philosophy of Science 66: 1–49CrossRefGoogle Scholar
  11. French S. (2000) The reasonable effectiveness of mathematics: Partial structures and the application of group theory to physics. Synthese 125: 103–120CrossRefGoogle Scholar
  12. García A., Simari G. (2004) Defeasible logic programming: An argumentative approach. Theory and Practice of Logic Programming 4: 95–138CrossRefGoogle Scholar
  13. Ginsberg, M. (ed.) (1987) Readings in nonmonotonic reasoning. Morgan Kaufmann, Los Altos, CAGoogle Scholar
  14. Guth A. (1997) The inflationary universe. Addison-Wesley, Reading, MAGoogle Scholar
  15. Hempel C. (1965) Aspects of scientific explanation and other essays in the philosophy of science. Free Press, NYGoogle Scholar
  16. Hogan C., Kirshner R., Suntzeff N. (1999) Surveying space-time with supernovae. Scientific American 280(1): 28–33CrossRefGoogle Scholar
  17. Khoury J., Ovrut B., Steinhardt P., Turok N. (2001) The Ekpyrotic universe: Colliding branes and the origin of the hot big bang. Physical Review D 64: 123522CrossRefGoogle Scholar
  18. Kuhn T. (1962) The structure of scientific revolutions. University of Chicago Press, Chicago, ILGoogle Scholar
  19. Lakatos I. (1978) The methodology of scientific research programmes. Cambridge University Press, Cambridge, UKGoogle Scholar
  20. Lakatos I., Musgrave A. (1970) Criticism and the growth of knowledge. Cambridge University Press, Cambridge, UKGoogle Scholar
  21. Lederman L., Schramm D. (1995) From quarks to the cosmos: Tools of discovery. Scientific American Library, NYGoogle Scholar
  22. Loui R. (1986) Defeat among arguments: A system of defeasible inference. Computational Intelligence 3(3): 100–106Google Scholar
  23. Loui R. (1991) Dialectic, computation and ampliative inference. In: Cummins R., Pollock J. (eds) Philosophy and AI. MIT Press, Cambridge, MAGoogle Scholar
  24. Loui R. (1998) Process and policy: Resource-bounded non-demonstrative reasoning. Computational Intelligence 14(1): 1–38CrossRefGoogle Scholar
  25. Mikenberg I., da Costa N. C. A., Chuaqui R. (1986) Pragmatic truth and approximation to truth. Journal of Symbolic Logic 51: 201–221CrossRefGoogle Scholar
  26. Penrose R. (1989) Difficulties with inflationary. Cosmology Annals of the New York Academy of Sciences 271: 249–264CrossRefGoogle Scholar
  27. Pollock J. (1991) A theory of defeasible reasoning. International Journal of Intelligent Systems 6: 33–54CrossRefGoogle Scholar
  28. Polya G. (1954) Mathematics and plausible reasoning. Princeton University Press, Princeton, N.J.Google Scholar
  29. Poole, D. (1985). On the comparison of theories: Preferring the most specific explanation. In Proceedings of the ninth international joint conference on artificial intelligence. Los Altos, CA: Morgan Kaufmann, Los Altos, CA.Google Scholar
  30. Popper K. (1959) The logic of scientific discovery. Hutchinson, LondonGoogle Scholar
  31. Prakken H., Vreeswijk G. (2001) Logics for defeasible argumentation. In: Gabbay D., Guenthner F. (eds) Handbook of philosophical logic, Vol. 4 (2nd ed.). Kluwer, Dordrecht, The NetherlandsGoogle Scholar
  32. Schwarzschild B. (2003) WMAP Spacecraft maps the entire cosmic microwave sky with unprecedented precision. Physics Today 56(4): 21–22CrossRefGoogle Scholar
  33. Simari G., Loui R. (1992) A mathematical treatment of defeasible reasoning and its implementation. Artificial Intelligence 53: 127–157CrossRefGoogle Scholar
  34. Skalski V., Sukenik M. (1992) Radiation of the cosmic background. Applied Space Science 187: 155–160CrossRefGoogle Scholar
  35. Stalnaker R. (1984) Inquiry. MIT Press, Cambridge, MAGoogle Scholar
  36. Suppe F. (1977) The structure of scientific theories. University of Illinois Press, Urbana, ILGoogle Scholar
  37. Thagard P. (1993) Computational Philosophy of Science. MIT Press, Cambridge, MAGoogle Scholar
  38. van der Hoek, W., Meyer, J., Tan, Y., Witteveen, C. (eds) (1992) Non-monotonic reasoning and partial semantics. Ellis Horwood, Chichester, Chichester, U.K.Google Scholar
  39. Vreeswijk G. (1997) Abstract argumentation systems. Artificial Intelligence 90: 225–279CrossRefGoogle Scholar
  40. Weinberg S. (1992) Dreams of a final theory. Pantheon Books, NYGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Fernando Tohmé
    • 1
  • Claudio Delrieux
    • 2
  • Otávio Bueno
    • 3
  1. 1.Departamento de EconomíaUniversidad Nacional del Sur, CONICETBahía, BlancaArgentina
  2. 2.Departamento de Ingeniería Eléctrica y de ComputadorasUniversidad Nacional del SurBahía, BlancaArgentina
  3. 3.Department of PhilosophyUniversity of MiamiCoral GablesUSA

Personalised recommendations