Skip to main content
Log in

Inductive learning by machines

  • Published:
Philosophical Studies Aims and scope Submit manuscript

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

References

  • Blum, L. and Blum, M. 1975, ‘Toward a mathematical theory of inductive inference’. Information and Control, 28, 125–155.

    Google Scholar 

  • Buchanan, B. G. and Mitchell, T. M. 1978, ‘Model-directed learning of production rules’, Waterman, D. A. and Hayes-Roth, F., (Eds.) Pattern-directed inference systems (Academic Press, New York).

    Google Scholar 

  • De Jong, G. 1981, ‘Generalizations based on explanations’, Proceedings of the Seventh International Joint Conference on Artificial Intelligence (Morgan Kaufmann, Vancouver, BC), pp. 67–69.

    Google Scholar 

  • Dietterich, T. G. 1986, ‘Learning at the knowledge level’, Machine Learning, 1(3).

  • Einstein, A. 1936, ‘Physics and reality’, Journal of the Franklin Institute, 221.

  • Feyerabend, P. 1970, Against method (New Left Books, London).

    Google Scholar 

  • Gold, E. M. 1967, ‘Language identification in the limit’, Information and Control, 10, pp. 447–474.

    Google Scholar 

  • Goodman, N. 1955, Fact, fiction and forest (Harvard University Press, Cambridge, MA).

    Google Scholar 

  • Hesse, M. 1980, Revolutions and reconstructions in the philosophy of science (Indiana University Press, Bloomington).

    Google Scholar 

  • Kemeny, J. G. 1953, ‘The use of simplicity in induction’, Philosophical Review, 62, pp. 391–408.

    Google Scholar 

  • Kolmogorov, A. N. 1965, ‘Three approaches to the quantitative definition of information’, Problems in Information Transmission, 1(1), pp. 1–7.

    Google Scholar 

  • Kuhn, T. S. 1970, The structure of scientific revolutions (Chicago University Press, Chicago, IL).

    Google Scholar 

  • Lakatos, I., and Musgrave, A. (Eds.), 1968, Problems in the philosophy of science. (North Holland, Amsterdam).

    Google Scholar 

  • Li, M., and Vitanyi, P. M. B. 1989, An introduction to Kolmogorov complexity and its applications (ACM Press, New York).

    Google Scholar 

  • Miller, D. 1974, ‘Popper's qualitative theory of verisimilitude’, British Journal for the Philosophy of Science, 25, pp. 178–88.

    Google Scholar 

  • Mitchell, Tom M. 1982, ‘Generalization as search’, Artificial Intelligence, 18(2), 203–226.

    Google Scholar 

  • Mitchell, T. M., Keller, R. M. & Kedar-Cabelli, S. T. 1986, ‘Explanation-based generalization: A unifying view’, Machine Learning, 1, 47–80.

    Google Scholar 

  • Muggleton, S. H. 1988, ‘A strategy for constructing new predicates in first-order logic’, Proceedings of the Third European Working Session on Learning (Pitman, Glasgow, Scotland), pp. 123–130.

    Google Scholar 

  • Muggleton, S. H. and Buntine, W. 1988, ‘Machine invention of first-order predicates by inverting resolution’, In Proceedings of the Fifth International Machine Learning Conference (Morgan Kaufmann, Ann Arbor, Michigan).

    Google Scholar 

  • Newton-Smith, W. H. 1981, The rationality of science (Routledge and Kegan Paul, London).

    Google Scholar 

  • Pearl, J. 1978, ‘On the connection between the complexity and credibility of inferred models’, International Journal of General Systems, 4, pp. 255–64.

    Google Scholar 

  • Pollock, J. L. 1986, Contemporary theories of knowledge. (Rowman and Littlefield, Totowa, NJ).

    Google Scholar 

  • Pollock, J. L. 1990, Nomic probability and the foundations of induction. (Oxford University Press).

  • Popper, K. R. 1968a, The logic of scientific discovery. (Hutchinson, London).

    Google Scholar 

  • Popper, K. R. 1968b, ‘Is there an epistemological problem of perception?’, (Lakatos & Musgrave, 1968), pp. 163–4.

  • Quine, W. v. O. 1960, Word and object (MIT Press, Cambridge, MA).

    Google Scholar 

  • Quine, W. v. O. & Ullian J. S. 1970, The web of belief (Random House, New York).

    Google Scholar 

  • Rivest, R. L. and Schapire, R. E. 1987, ‘A new approach to unsupervised learning in deterministic environments’, Proceedings of the Fourth International Workshop on Machine Learning (Morgan Kaufmann, Irvine, CA).

    Google Scholar 

  • Robinson, J. A. 1965, ‘A machine-oriented logic based on the resolution principle’, Journal of the ACM, 12(1), pp. 23–40.

    Google Scholar 

  • Russell, S. J. 1986, ‘Preliminary steps toward the automation of induction’, Proceedings of the Fifth National Conference on Artificial Intelligence (Morgan Kaufmann, Philadelphia, PA).

    Google Scholar 

  • Russell, S. J. 1988, ‘Tree-structured bias’, Proceedings of the Seventh National Conference on Artificial Intelligence (Morgan Kaufmann, Minneapolis, MN).

    Google Scholar 

  • Russell, S. J. 1989, The use of knowledge in analogy and induction (Pitman, London).

    Google Scholar 

  • Solomonoff, R. J. 1964, ‘A formal theory of inductive inference (parts I and II)’, Information and Control, 7, pp. 1–22, 224–54.

    Google Scholar 

  • Suppes, P. 1968, ‘Information processing and choice behaviour’, (Lakatos & Musgrave, 1968), pp. 278–99.

  • Tichy, P. 1974, ‘On Popper's definition of verisimilitude’, British Journal for the Philosophy of Science, 25, pp. 155–60.

    Google Scholar 

  • Valiant, L. G. 1984, ‘A theory of the learnable’, Communications of the ACM, 27, pp. 1134–1142.

    Google Scholar 

  • Warmuth, M. (Ed.), 1989, Proceedings of the Second International Workshop on Computational Learning Theory (Morgan Kaufmann, Santa Cruz, CA).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

The research described herein has been supported by funding from the Lockheed AI Center and the California MICRO Program. The author would also like to thank Benjamin Grosof, John Pollock, Devika Subramanian, Thomas Dietterich and Steven Muggleton for their valuable comments and suggestions.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Russell, S. Inductive learning by machines. Philosophical Studies 64, 37–64 (1991). https://doi.org/10.1007/BF00356089

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00356089

Keywords

Navigation