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Identifiable Collections of Countable Structures

Published online by Cambridge University Press:  01 April 2022

Daniel N. Osherson
Affiliation:
Department of Brain and Cognitive Sciences Massachusetts Institute of Technology
Scott Weinstein
Affiliation:
Department of Philosophy University of Pennsylvania

Abstract

A model of idealized scientific inquiry is presented in which scientists are required to infer the nature of the structure that makes true the data they examine. A necessary and sufficient condition is presented for scientific success within this paradigm.

Type
Research Article
Copyright
Copyright © 1989 by the Philosophy of Science Association

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Footnotes

Support for this research was provided by the System Development Foundation.

References

REFERENCES

Glymour, C. (1984), “Inductive Inference in the Limit”, Erkenntnis 21.CrossRefGoogle Scholar
Osherson, D., Stob, M., and Weinstein, S. (1986), Systems That Learn. Cambridge: MIT Press.Google Scholar
Osherson, D., and Weinstein, S. (1986), “Identification in the Limit of First Order Structures”, Journal of Philosophical Logic 15: 5581.CrossRefGoogle Scholar
Shapiro, E. (1981), “An Algorithm That Infers Theories from Facts”, Proceedings of the Seventh International Joint Conference on Artificial Intelligence, IJCAI.Google Scholar