Skip to main content
Log in

Automated Discovery Systems and Scientific Realism

  • Published:
Minds and Machines Aims and scope Submit manuscript

Abstract

In the paper I explore the relations between a relatively new and quickly expanding branch of artificial intelligence –- the automated discovery systems –- and some new views advanced in the old debate over scientific realism. I focus my attention on one such system, GELL-MANN, designed in 1990 at Wichita State University. The program's task was to analyze elementary particle data available in 1964 and formulate an hypothesis (or hypotheses) about a `hidden', more simple structure of matter, or to put it in contemporary terms –- the discovery of quarks. The central thesis of my paper is that systems like GELL-MANN not only discover (or rediscover) the hidden structure of matter, but also provide independent strong evidence in favor of scientific realism about entities involved in that structure. I make an attempt to show how an argument for scientific realism about sub-microscopic entities can be constructed that would parallel Ian Hacking's `argument from coincidence' presented with respect to microscopic objects in his famous book Representing and Intervening.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Białkowski, G. and Sosnowski, R. (1971), Cząstki elementarne [Elementary Particles], Warszawa: PWN.

    Google Scholar 

  • Bradshaw, G.L, Langley, P. and Simon, H. (1980), wBACON.4: The Discovery of Intrinsic Properties', in Proceedings of the Third Biennial Conference of the Canadian Society for Computational Studies of Intelligence, Victoria: BC, pp. 19–25.

    Google Scholar 

  • Cartwright, N. (1983), How the Laws of Physics Lie?, Oxford: Clarendon Press.

    Google Scholar 

  • Fisher, P. and Żytkow, J.M. (1990), 'Discovering Quarks and Hidden Structure', in Ras, Z., Zemankova, M. and Emrich, M.L., eds., Methodologies for Intelligent Systems 5, New York: Elsevier Science, pp. 362–370.

    Google Scholar 

  • Gell-Mann, M. and Ne'eman, Y. (1964), The Eightfold Way, NewYork: Benjamin.

    Google Scholar 

  • Gerwin, D.G. (1974), 'Information Processing, Data inferences, and Scientific Generalization', Behavioral Sciences 19, pp. 314–325.

    Google Scholar 

  • Giza, P. (1987), 'How to Defend Realism?', in Proceedings of the 11th International Wittgenstein Symposium, Kirchberg, Austria, pp. 39–43.

  • Halzen, F., (1984), Quarks and Leptons: An Introductory Course in Modern Particle Physics, New York: Wiley.

    Google Scholar 

  • Hammermesh, M. (1963), Group Theory, New York: Addison-Wesley.

    Google Scholar 

  • Langley, P. and Nordhausen, B. (1986), 'A Framework for Empirical Discovery', in Proceedings of the International Meeting on Advances in Learning, Les Arcs, France.

  • Langley, P. and Ż ytkow, J.M. (1989), 'Data-Driven Approaches to Empirical Discovery', Artificial Intelligence 40, pp. 283–312.

    Google Scholar 

  • Langley, P., Simon, H., Bradshaw, G.L. and Żytkow, J.M. (1987), Scientific Discovery: Computational Explorations of the Creative Processes, Cambridge, MA: MIT Press.

    Google Scholar 

  • Norwood, J. (1975), Twentieth Century Physics, New York: Prentice Hall.

    Google Scholar 

  • Rose, D. (1989), 'Using Domain Knowledge to Aid Scientific Theory Revision', in Proceedings of the Sixth International Workshop on Machine Learning, San Mateo, CA: Morgan Kaufmann Publishers, pp. 272–277.

    Google Scholar 

  • Wigner, E. (1958), Group Theory and its Application to Quantum Mechanics of Atomic Spectra, New York.

  • Żytkow, J.M. (1987), 'Combining Many Searches in the FAHRENHEIT Discovery System', in Proceedings of the Fourth International Workshop on Machine Learning, Irvine CA, pp. 281–287.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Giza, P. Automated Discovery Systems and Scientific Realism. Minds and Machines 12, 105–117 (2002). https://doi.org/10.1023/A:1013726012949

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1013726012949

Navigation