Skip to main content
Log in

Introduction: Machine Learning as Philosophy of Science

  • Published:
Minds and Machines Aims and scope Submit manuscript

Abstract

I consider three aspects in which machine learning and philosophy of science can illuminate each other: methodology, inductive simplicity and theoretical terms. I examine the relations between the two subjects and conclude by claiming these relations to be very close.

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.

Similar content being viewed by others

References

  • Bensusan, H.(1999), Automatic Bias Learning:An Inquiry into the Inductive Bias of Induction, PhD dissertation, University of Sussex.

  • Carnap, R.(1962), Logical Foundations of Probability, 2nd edition, Chicago: University of Chicago.

    Google Scholar 

  • Craig, W.(1956), 'Replacement of Auxiliary Expressions', Philosophical Review 65, pp.38-55.

    Google Scholar 

  • Dai, H., Korb, K.B., Wallace, C.S.and Wu, W.(1997), 'A Study of Casual Discovery with Weak Links and Small Samples', in Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, San Francisco, CA: Morgan Kaufmann, pp.1304-1309.

    Google Scholar 

  • Dreyfus, H.(1992), What Computers Still Can 't Do:A Critique of Artificial Reason, 3rd edition, Cambridge, MA: MIT Press.

    Google Scholar 

  • Franklin, A.(1990), Experiment, Right or Wrong, Cambridge: Cambridge University.

    Google Scholar 

  • George., M.P.and Wallace, C.S.(1984), 'A General Selection Criterion for Inductive Inference ', European Conference on Artificial Intelligence, pp.473-482.

  • Giere, R.(1973), 'History and Philosophy of Science:Marriage of Convenience or Intimate Relationship?', British Journal for the Philosophy of Science 24, pp.282-297.

    Google Scholar 

  • Glymour, C.and Cooper, G.(eds.)(1999), Computation, Causation, and Discovery, Cambridge, MA: MIT Press.

    Google Scholar 

  • Hacking, I.(1983), Representing and Intervening, Cambridge: Cambridge University.

    Google Scholar 

  • Hempel, C.(1958), 'The Theoretician 's Dilemma ', in H.Feigl, M. Scriven and G.Maaxwell, eds., Minnesota Studies in the Philosophy of Science, Minneapolis: University of Minnesota Press.

    Google Scholar 

  • Howson, C.and Urbach, P.(1993), Scientific Reasoning:The Bayesian Approach, 2nd edition, Chicago: Open Court.

    Google Scholar 

  • Hume, D.(1739/1888), in L.A. Selby-Bigge, ed., A Treatise of Human Nature, Oxford: Clarendon.

    Google Scholar 

  • Humphreys, P.and Freedman, D.(1996), 'The Grand Leap ', British Journal for Philosophy of Science 47, pp.113-123.

    Google Scholar 

  • Korb, K.B.(1992), A Bayesian Platform for Automating Scientific Induction, PhD dissertation, Indiana University.

  • Korb, K.B.(1995), 'Inductive Learning and Defeasible Inference', Journal of Experimental and Theoretical Artificial Intelligence 7, pp.291-324.

    Google Scholar 

  • Korb, K.B.(1996), 'Symbolicism and Connectionism:AI Back at a Join Point ', in Proceedings of the Conference, ISIS '96 Information, Statistics and Induction in Science, Singapore: World Scientific, pp.247-257.

    Google Scholar 

  • Korb, K.B.and Nicholson, A.E.(2004), Bayesian Artificial Intelligence, Boca Raton: Chapman Hall/CRC Press.

    Google Scholar 

  • Korb, K.B.and Wallace, C.S.(1997), 'In Search of the Philosopher 's Stone:Remarks on Humphreys and Freedman 's Critique of Causal Discovery', British Journal for Philosophy of Science 48, pp.543-553.

    Google Scholar 

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

    Google Scholar 

  • Laudan, L.(1987), 'Progress or Rationality?The Prospects for Normative Naturalism', American Philosophical Quarterly 24, pp.19-31.

    Google Scholar 

  • McCarthy, J.(1968), 'Programs with Common Sense ', in M.Minsky, ed., Semantic Information Processing, Cambridge, MA: MIT Press, pp.403-418.

    Google Scholar 

  • McDermott, D.(1987), 'A Critique of Pure Reason ', Computational Intelligence 3, pp.151-160.

    Google Scholar 

  • Mascaro, S., Korb, K.B.and Nicholson, A.E.(2001), 'Suicide as an Evolutionarily Stable Strategy ', in J. Kelemen and P. Sosik, eds., Proceedings of the 6th European Conference on Advances in Artificial Life-ECAL 2001, Heidelberg: Springer-Verlag, pp.120-132.

    Google Scholar 

  • Ramsey, F.P.(1931), in R.B. Braithwaite, ed., The Foundations of Mathematics and Other Logical Essays, New York: Humanities Press.

    Google Scholar 

  • Reichenbach, H.(1949), The Theory of Probability, 2nd edition, Berkeley: University of California.

    Google Scholar 

  • Schaffer, C.(1994), 'A Conservation Law for Generalization Performance ', in Proceedings of the 11th International Conference on Machine Learning, pp.259-265.

  • Simon, H.(1983), 'Why Should Machines Learn?'in R.S. Michalski, J.G. Carbonell and T.M. Mitchell, eds., Machine Learning, pp.25-37.

  • Slezak, P.(1989), 'Scientific Discovery by Computer as Refutation of the Strong Programme', Social Studies of Science 19, pp.563-600.

    Google Scholar 

  • Sneed, J.(1979), The Logical Structure of Mathematical Physics, Dordrecht: D.Reidel.

    Google Scholar 

  • Solomono., R.(1964), 'A Formal Theory of Inductive Inference, I and II ', Information and Control 7, pp.1-22, 224-254.

    Google Scholar 

  • Strawson, P.(1999), 'Dissolving the Problem of Induction ', in L.P. Pojman, ed., The Theory of Knowledge, 2nd edition, Belmont, CA: Wadsworth Publishing, pp.502-506

    Google Scholar 

  • Thagard, P.(1988), Computational Philosophy of Science, Cambridge, MA: MIT Press.

    Google Scholar 

  • Wolpert, D.H.and Macready, W.G.(1995), No Free Lunch Theorems for Search, Santa Fe Institute Technical Report, 95-02-010.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Korb, K.B. Introduction: Machine Learning as Philosophy of Science. Minds and Machines 14, 433–440 (2004). https://doi.org/10.1023/B:MIND.0000045986.90956.7f

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/B:MIND.0000045986.90956.7f

Navigation