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Computational Models in the Philosophy of Science

Published online by Cambridge University Press:  28 February 2022

Paul Thagard
Paul Thagard*
Affiliation:
Princeton University
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Extract

This paper is a summary of my oral presentation at PSA 86. Since that presentation was in turn a summary of views that will appear in great detail elsewhere (Thagard forthcoming), I shall be very brief here. My aim is to outline how computational models can provide the same benefits to the philosophy of science that they currently provide to cognitive psychology. I shall begin by situating an enterprise that I call computational philosophy of science in relation to the more familiar fields of historical philosophy of science, artificial intelligence, and cognitive psychology. After some general remarks about the use of computational models, I shall describe a particular model of problem solving and learning that has been used to simulate the discovery and justification of the wave theory of sound.

Type
Part IX. Epistemology
Information
PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association , Volume 1986 , Issue 2: Volume Two: Symposia and Invited Papers 1986 , 1986 , pp. 329 - 335
Copyright
Copyright © 1987 by the Philosophy of Science Association

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References

Anderson, J. (1983) The Architecture of Cognition. Cambridge, MA: Harvard University Press.Google Scholar
Barr, A. and Feigenbaum, E. (eds.). (1981) Handbook of Artificial Intelligence. Los Altos: Kaufmann.Google Scholar
Glymour, C. (1980) Theory and Evidence. Princeton: Princeton University Press.Google Scholar
Goldman, A. (1986) Cognition and Epistemology. Cambridge, MA: Harvard University Press.Google Scholar
Hempel, C. (1965) Aspects of Scientific Explanation. New York: The Free Press.Google Scholar
Holland, J., Holyoak, K., Nisbett, R. and Thagard, P. (1986) Induction: Processes of Inference, Learning, and Discovery. Cambridge MA: Bradford Books/MIT Press.Google Scholar
Kuhn, T. (1970) The Structure of Scientific Revolutions (2nd edn.). Chicago: University of Chicago Press.Google Scholar
Laudan, L. (1979) “Historical Methodologies: An Overview and Manifesto.” In Current Research in the Philosophy of Science. Edited by Asquith, P. and Kyburg, H.. East Science: Philosophy of Association. Pages 40-54.Google Scholar
McCarthy, J. (1980) “Circumscription—A Form of Non-Monotonic Reasoning.” Artificial Intelligence 13: 27-39.CrossRefGoogle Scholar
Minsky, M. (1975). “A Framework for Representing Knowledge”. In The Psychology of Computer Vision. Edited by Winston, P.. New York: McGraw-Hill. Pages 211-277.Google Scholar
Newell, A. and Simon, H. (1972) Human Problem Solving. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Salmon, W. (1984) Scientific Explanation and the Causal Structure of the World. Princeton: Princeton University Press.Google Scholar
Sambursky, S. (1973) Physics of the Stoics. Westport, CT: Greenwood Press.Google Scholar
Thagard, P. (1978) “The Best Explanation: Criteria for Theory Choice.” Journal of Philosophy 75: 76-92.CrossRefGoogle Scholar
Thagard, P. (1984a) “Conceptual Combination and Scientific Discovery.” In PSA 1984, vol. 1. Edited by Asquith, P. and Kitcher, P. East Lansing: Philosophy of Science Association. Pages 3-12.Google Scholar
Thagard, P. (1984b) “Frames, Knowledge, and Inference.” Synthese 61: 233-259.CrossRefGoogle Scholar
Thagard, P. (forthcoming). Computational Philosophy of Science. Cambridge, MA: Bradford Books/MIT Press.CrossRefGoogle Scholar
Whewell, W. (1967) The Philosophy of the Inductive Sciences. New York: Johnson Reprint Corp.Google Scholar
Wirth, N. (1976) Algorithms + Data Structures = Programs. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar