Advertisement

Using Conceptual Spaces to Model the Dynamics of Empirical Theories

  • Peter Gärdenfors
  • Frank Zenker
Chapter
Part of the Logic, Epistemology, and the Unity of Science book series (LEUS, volume 21)

Abstract

In Conceptual Spaces (Gärdenfors 2000), dimensions and their relations provide a topological representation of a concept’s constituents and their mode of combination. When concepts are modeled as n-dimensional geometrical structures, conceptual change denotes the dynamic development of these structures. Following this basic assumption, we apply conceptual spaces to the dynamics of empirical theories. We show that the terms of the structuralist view of empirical theories can be largely recovered. Based on the logically possible change operations which a concept’s dimensions can undergo (singularly or in combination), we identify four types of (increasingly radical) change to an empirical theory. The incommensurability issue as well as the importance of measurement procedures for the identification of a radical theory change are briefly discussed.

Keywords

Belief Revision Intended Application Theory Element Theory Change Conceptual Space 
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.

Notes

Acknowledgements

We would like to thank the organizer and the audience of the Science in Flux workshop at Lund University and, especially with respect to our exposition of structuralism, J. D. Sneed and C. U. Moulines for helpful comments and criticism. Frank Zenker acknowledges funding from the Swedish Institute (SI) and Peter Gärdenfors from the Swedish Research Council.

References

  1. Balzer, W., D.A. Pearce, and H.-J. Schmidt. 1984. Reduction in science. Structure, examples, philosophical problems (Synthese Library Vol. 175). Dordrecht: Reidel.Google Scholar
  2. Balzer, W., C.U. Moulines, and J.D. Sneed. 1987. An architectonic for science. The structuralist program. (Synthese Library Vol. 186). Dordrecht: Reidel.Google Scholar
  3. Balzer, W., C.U. Moulines, and J.D. Sneed. (eds.). 2000. Structuralist knowledge representation. Paradigmatic examples. Amsterdam: Rodopi.Google Scholar
  4. Batitsky, V. 2000. Measurement in Carnap’s late philosophy of science. Dialectica 54:87–108.CrossRefGoogle Scholar
  5. BIPM. 1901. Comptes Rendus de la 3e Conférence Générale des Poids et Mesures, Paris 1901. http://www1.bipm.org/en/CGPM/db/3/2/
  6. Carnap, R. 1971. A basic system of inductive logic, part 1. In Studies in inductive logics and probability, vol. 1, eds. R. Carnap, and R.C. Jeffrey, 35–165. Berkeley, CA: UCP.Google Scholar
  7. Chang, H. 2004. Inventing temperature. Measurement and scientific progress. Oxford: OUP.Google Scholar
  8. Chen, X. 2003. Why did John Herschel fail to understand polarization? The differences between object and event concepts. Studies in the History and Philosophy of Science 34:491–513.CrossRefGoogle Scholar
  9. Diederich, W. 1996. Pragmatic and diachronic aspects of structuralism. In Structuralist theory of science. Focal issues, new results, eds. W. Balzer, and C.U. Moulines, 75–82. New York, NY: De Gruyter.Google Scholar
  10. DiSalle, R. 2006. Understanding space time. The philosophical development from Newton to Einstein. Cambridge: CUP.Google Scholar
  11. Ellis, B. 1968. Basic concepts of measurement. Cambridge: CUP.Google Scholar
  12. Gähde, U. 1997. Anomalies and the revision of theory-elements: Notes on the advance of Mercury’s perihelion. In Structures and norms in science. vol. 2 (Synthese Library Vol. 260), eds. M. L. Dalla Chiara. et al., 89–104. Dordrecht: Kluwer.Google Scholar
  13. Gähde, U. 2002. Holism, underdetermination, and the dynamics of empirical theories. Synthese 130:69–90.CrossRefGoogle Scholar
  14. Gärdenfors, P. 1988. Knowledge in flux: Modeling the dynamics of epistemic states. Cambridge, MA: MIT Press.Google Scholar
  15. Gärdenfors, P. 2000. Conceptual spaces. Cambridge, MA: MIT Press.Google Scholar
  16. Garner, W.R. 1970. The processing of information and structure. Potomac: Wiley, New York, NY: Erlbaum.Google Scholar
  17. Kuhn, T. 1962/1970. The structure of scientific revolution. Chicago: CUP.Google Scholar
  18. Kuhn, T. 1976. Theory change as structure change. Comments on the sneed formalism. Erkenntnis 10:179–199.CrossRefGoogle Scholar
  19. Kuhn, T. 1987. What are scientific revolutions? In The Probabilistic revolution. vol. 1, eds. L. Krüger, et al., 7–22. Cambridge: MIT Press.Google Scholar
  20. Maddox, W.T. 1992. Perceptual and decisional separability. In Multidimensional models of perception and cognition, ed. G. F. Ashby, 147–180. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  21. Melara, R.D. 1992. The concept of perceptual similarity: From psychophysics to cognitive psychology. In Psychophysical approaches to cognition, ed. D. Algom, 303–388. Amsterdam: Elsevier.Google Scholar
  22. Moulines, C.U. 2002. Introduction: Structuralism as a program for modeling theoretical science (special issue on structuralism). Synthese 130:1–11.CrossRefGoogle Scholar
  23. Roseveare, N.T. 1982. Mercury’s perihelion from LeVerrier to Einstein. Oxford: Clarendon.Google Scholar
  24. Sneed, J.D. 1971. The logical structure of mathematical physics. Dordrecht: Reidel.Google Scholar
  25. Stegmüller, W. 1976. The structuralist view of theories. Berlin: Springer.Google Scholar
  26. Stevens, S.S. 1946. On the theory of scales of measurement. Science 103:677–680.CrossRefGoogle Scholar
  27. Suppes, P. 1957. Introduction to logic. New York, NY: Van Nostrand.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of PhilosophyUniversity of LundLundSweden

Personalised recommendations