Skip to main content

Learning Theory and Epistemology

  • Chapter
Handbook of Epistemology

Abstract

Learning is the acquisition of new knowledge and skills. It spans a range of processes from practice and rote memorization to the invention of entirely novel abilities and scientific theories that extend past experience. Learning is not restricted to humans: machines and animals ran learn, social organizations can learn, and a genetic population can learn through natural selection. In this broad sense, learning is adaptive change, whether in behavior or in belief.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 509.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 649.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 649.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Angluin, D.: 1987, `Learning Regular Sets from Queries and Counterexamples’, Information and Computation 75, 87–106.

    Article  Google Scholar 

  • Angluin, D.: 1989, Inductvive Inference of Formal Languages from Positive Data’, Information and Control 49, 117–135.

    Google Scholar 

  • Blum, M. and L. Blum: 1975, `Toward a Mathematical Theory of Inductive Inference’, Information and Control 28, 125–155.

    Article  Google Scholar 

  • Bonjour, L.: 1985, The Structure of Empirical Knowledge, Harvard University Press, Cambridge.

    Google Scholar 

  • Brown, R. and C. Hanlon: 1970, `Derivational Complexity and the Order of Acquisition of Child Speech’, in J. Hayes (ed.), Cognition and the Development of Language, Wiley, New York.

    Google Scholar 

  • Carnap, R.: 1950, The Logical Foundations of Probability,University of Chicago Press, Chicago.

    Google Scholar 

  • Case, J. and C. Smith: 1983, `Comparison of Identification Criteria for Machine Inductive Inference’, Theoretical Computer Science 24, 193–220.

    Article  Google Scholar 

  • DeFinetti: 1990, The Theory of Probability, Wiley, New York.

    Google Scholar 

  • Glymour, C.: 1980, Theory and Evidence,MIT Press, Cambridge.

    Google Scholar 

  • Gold, F. M.: 1965, `Limiting Recursion’, Journal of Symbolic Logic 30, 27–48.

    Google Scholar 

  • Gold, E. M.: 1967, `Language Identification in the Limit’, Information and Control 10, 447474.

    Google Scholar 

  • Halmos, P.: 1974, Measure Theory,Springer, New York.

    Google Scholar 

  • Hinman P • 1978, Recursion Theoretic Hierarchies, Springer, New York.

    Google Scholar 

  • James, W.: 1948, `The Will to Believe’, in A. Castell (ed.), Essays in Pragmatism, Collier Macmillan, New York.

    Google Scholar 

  • Kearns, M. and L. Valiant: 1994, `Cryptographic limitations on learning boolean formulae and finite automata’, Journal of the ACM. 41, 57–95.

    Google Scholar 

  • Kearns, M. and U. Vazirani: 1994, An Introduction to Computational Learning Theory, MIT Press, Cambridge.

    Google Scholar 

  • Kelly, K.: 1992, “Learning Theory and Descriptive Set Theory”, Logic and Computation 3, 27–45.

    Article  Google Scholar 

  • Kelly, K.: 1996, The Logic of Reliable Inquiry, Oxford University Press, New York.

    Google Scholar 

  • Kelly, K. and C. Glymour: 1989, `Convergence to the Truth and Nothing But the Truth’, Philosophy of Science 56, 185–220.

    Article  Google Scholar 

  • Kelly, K. and C. Glymour: 1990, `Theory Discovery from Data with Mixed Quantifiers’, Journal of Philosophical Logic 19, 1–33.

    Article  Google Scholar 

  • Kelly. K. and C. Glymour: 1992, `Inductive Inference from Theory-Laden Data’, Journal of Philosophical Logic 21, 391–444.

    Article  Google Scholar 

  • Kelly, K. and O. Schulte: 1995, `The Computable Testability of Theories Making Uncomputable Predictions’, Erkenntnis 43, 29–66.

    Article  Google Scholar 

  • Kelly K. and O. Schulte: 1997, `Church’s Thesis and Hume’s Problem, in M. L. Dalla Chiara et. al. (eds.), Logic and Scientific Methods, Kluwer, Dordrecht.

    Google Scholar 

  • Kemeny, J.: 1953, `The Use of Simplicity in Induction’, Philosophical Review 62, 391–408. Kugel, P.: 1977, `Induction Pure and Simple’, Information and Control 33, 236–336.

    Google Scholar 

  • Lauth, B.: 1993, `Inductive Inference in the Limit for First-Order Sentences’, Studia Logica 52, 491–517.

    Article  Google Scholar 

  • Lehrer, K.: 1990, Theory of Knowledge, Westview, San Francisco.

    Google Scholar 

  • Levi, I.: 1991, The Fixation of Belief and It’s Undoing, Cambridge University Press, Cambridge.

    Book  Google Scholar 

  • Miller, D.: 1974, `On Popper’s Definitions of Verisimilitude’, British Journal of the Philosophy of Science 25, 155–188.

    Article  Google Scholar 

  • Mormann, T.: 1988, `Are All False Theories Equally False?’, British Journal for the Philosophy of Science 39, 505–519.

    Article  Google Scholar 

  • Neyman, J. and E. Pearson: 1933: `On the Problem of the Most Efficient Tests of Statistical Hypotheses’, Philosohical Transactions of the Royal Society 231 A, 289–337.

    Google Scholar 

  • Osherson, D. and S. Weinstein: 1986, Systems that Learn, MIT Press, Cambridge.

    Google Scholar 

  • Osherson, D. and S. Weinstein: 1987, `Paradigms of Truth Detection’, Journal of Philosophical Logic 18, 1–41.

    Article  Google Scholar 

  • Osherson, D. and S. Weinstein: 1988, `Mechanical Learners Pay a Price for Bayesianism’, Journal of Symbolic Logic 56, 661–672.

    Article  Google Scholar 

  • Osherson, D. and S. Weinstein: 1989, `Identification in the Limit of First Order Structures’, Journal of Philosophical Logic 15, 55–81.

    Google Scholar 

  • Osherson, D, and S. Weinstein: 1991, `A Universal Inductive Inference Machine’, Journal of Symbolic Logic 56, 661–672.

    Article  Google Scholar 

  • Popper, K.: 1982, Unended Quest: an Intellectual Autobiography, Open Court, LaSalle. Popper, K.: 1968, The Logic of Scientific Discovery, Harper, New York.

    Google Scholar 

  • Putnam, H.: 1963, “Degree of confirmation’ and inductive logic’, in A. Schilpp (ed.), The Philosophy of Rudolph Carnap,Open Court, LaSalle.

    Google Scholar 

  • Putnam, H.: 1965, `Trial and Error Predicates and a Solution to a Problem of Mostowski’, Journal of Symbolic Logic 30 49–57.

    Google Scholar 

  • Reichenbach, H.: 1938: Experience and Prediction,University of Chicago Press, Chicago. Savage, L.: 1972: The Foundations of Statistics,Dover, New York.

    Google Scholar 

  • Sextus Empiricus: 1985, Selections from the Major Writings on Scepticism, Man and God, P. Hallie (ed.), trans. S. Etheridge, Hackett, Indianapolis.

    Google Scholar 

  • Shapiro, E.: 1981, `Inductive Inference of Theories from Facts’, Report YLU 192, Department of Computer Science, Yale University, New Haven.

    Google Scholar 

  • Wexler, K. and P. Culicover: 1980, Formal Principles of Language Acquisition, MIT Press, Cambridge.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Kelly, K. (2004). Learning Theory and Epistemology. In: Niiniluoto, I., Sintonen, M., Woleński, J. (eds) Handbook of Epistemology. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-1986-9_5

Download citation

  • DOI: https://doi.org/10.1007/978-1-4020-1986-9_5

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-015-6969-9

  • Online ISBN: 978-1-4020-1986-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics