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Scientific Discovery from the Perspective of Hypothesis Acceptance

Published online by Cambridge University Press:  01 January 2022

Eric Martin  and
Daniel Osherson
Eric Martin*
Affiliation:
University of New South Wales
Daniel Osherson*
Affiliation:
Rice University
*
Martin: School of Computer Science and Engineering, The University of New South Wales, Sydney, NSW 2052, Australia, [email protected]; Osherson: Psychology Dept., MS-25, Rice University, P.O. Box 1892, Houston TX 77005–1892, [email protected]
Martin: School of Computer Science and Engineering, The University of New South Wales, Sydney, NSW 2052, Australia, [email protected]; Osherson: Psychology Dept., MS-25, Rice University, P.O. Box 1892, Houston TX 77005–1892, [email protected]
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Abstract

A model of inductive inquiry is defined within the context of first-order logic. The model conceives of inquiry as a game between Nature and a scientist. To begin the game, a nonlogical vocabulary is agreed upon by the two players, along with a partition of a class of countable structures for that vocabulary. Next, Nature secretly chooses one structure (“the real world”) from some cell of the partition. She then presents the scientist with a sequence of facts about the chosen structure. With each new datum the scientist announces a guess about the cell to which the chosen structure belongs. To succeed in his or her inquiry, the scientist's successive conjectures must be correct all but finitely often, that is, the conjectures must converge in the limit to the correct cell. Different kinds of scientists can be investigated within this framework. At opposite ends of the spectrum are dumb scientists that rely on the strategy of “induction by enumeration,” and smart scientists that rely on an operator of belief revision. We report some results about the scope and limits of these two inductive strategies.

Type
Research Article
Information
Philosophy of Science , Volume 69 , Issue S3 , September 2002 , pp. S331 - S341
Copyright
Copyright © The Philosophy of Science Association

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References

Alchourron, C. E., and Makinson, D. (1985), “On the Logic of Theory Change: Safe Contraction”, On the Logic of Theory Change: Safe Contraction 44:405–422.Google Scholar
Cohen, L. J. (1992), An Essay on Belief and Acceptance. Oxford: Oxford University Press.Google Scholar
Gardenfors, P. (1988), Knowledge in Flux: Modeling the Dynamics of Epistemic States. Cambridge, Mass.: MIT Press.Google Scholar
Hansson, S. O. (1994), “Kernel Contraction”, Kernel Contraction 59(3): 845–859.Google Scholar
Hansson, S. O. (1999), A Textbook of Belief Dynamics: Theory Change and Database Updating. Norwell, Mass.: Kluwer Academic Publishers.CrossRefGoogle Scholar
Jain, S., Osherson, D., Royer, J., and Sharma, A. (1999), Systems that Learn, 2nd ed. Cambridge, Mass.: MIT Press.CrossRefGoogle Scholar
Kelly, K., Schulte, O., and Hendricks, V. (1995), “Reliable Belief Revision”, in Proceedings of the XII Joint International Congress for Logic, Methodology and the Philosophy of Science (Florence, Italy). Dordrecht: Kluwer, 383–398.Google Scholar
Kelly, K. T. (1996), The Logic of Reliable Inquiry. New York: Oxford University Press.Google Scholar
Martin, E., and Osherson, D. (1998), Elements of Scientific Inquiry. Cambridge, Mass.: MIT Press.Google Scholar
Martin, E., and Osherson, D. (2000), “Scientific Discovery on Positive Data via Belief Revision”, Scientific Discovery on Positive Data via Belief Revision 29:483–506.Google Scholar
Martin, E., and Osherson, D. (2001), “Induction by Enumeration”, Induction by Enumeration 171:50–68.Google Scholar
Popper, K. (1959), The Logic of Scientific Discovery. London: Hutchinson.Google Scholar