Linked bibliography for the SEP article "Formal Learning Theory" by Oliver Schulte
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If everything goes well, this page should display the bibliography of the aforementioned article as it appears in the Stanford Encyclopedia of Philosophy, but with links added to PhilPapers records and Google Scholar for your convenience. Some bibliographies are not going to be represented correctly or fully up to date. In general, bibliographies of recent works are going to be much better linked than bibliographies of primary literature and older works. Entries with PhilPapers records have links on their titles. A green link indicates that the item is available online at least partially.
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- Abramsky, S., 1987. Domain Theory and the Logic of Observable
Properties, Ph.D. Dissertation, University of London. (Scholar)
- Apsitis, K., 1994. “Derived sets and inductive
inference”, in Proceedings of the 5th International Work on
Algorithmic Learning Theory, S. Arikawa, K.P. Jantke (eds.),
Berlin, Heidelberg: Springer, pp. 26–39. (Scholar)
- Baltag, A. and Smets, S., 2011. “Keep changing your beliefs, aiming for the truth”, Erkenntnis, 75(2): 255–270. (Scholar)
- Baltag, A., Gierasimczuk, N., Smets, S., 2015. “On the
Solvability of Inductive Problems: A Study in Epistemic
Topology”, Proceedings of the 15th Conference on Theoretical
Aspects of Rationality and Knowledge (TARK 2015), , pp.
65–74.
Electronic Proceedings in Theoretical Computer Science available online. (Scholar)
- Bub, J., 1994. “Testing Models of Cognition Through the Analysis of Brain-Damaged Performance”, British Journal for the Philosophy of Science, 45: 837–55. (Scholar)
- Carlucci, L., Case, J., Jain, S. and Stephan, F., 2005. “Non
U-shaped vacillatory and team learning”, in International
Conference on Algorithmic Learning Theory, Berlin, Heidelberg:
Springer, pp. 241–255. (Scholar)
- Chart, D., 2000. “Schulte and Goodman’s Riddle”,
British Journal for the Philosophy of Science, 51:
837–55. (Scholar)
- de Brecht, M. and Yamamoto, A., 2008. “Topological
properties of concept spaces”, in International Conference on
Algorithmic Learning Theory, Berlin, Heidelberg: Springer, pp.
374–388. (Scholar)
- Domingos, P., 1999. “The role of Occam’s razor in
knowledge discovery”, Data mining and Knowledge
discovery, 3(4): 409–425. (Scholar)
- Earman, J., 1992. Bayes or Bust?, Cambridge, Mass.: MIT Press. (Scholar)
- Feynman, R., 1965. The Character of Physical Law, Cambridge, Mass.: MIT Press; 19th edition, 1990. (Scholar)
- Friend, M. and N. Goethe and V. Harazinov (eds.), 2007.
Induction, Algorithmic Learning Theory, and Philosophy,
Dordrecht: Springer, pp. 111–144. (Scholar)
- Ford, K., 1963. The World of Elementary Particles, New
York: Blaisdell Publishing. (Scholar)
- Gärdenfors, P., 1988. Knowledge In Flux: modeling the dynamics of epistemic states, Cambridge, Mass.: MIT Press. (Scholar)
- Genin, K., 2018. “The Topology of Statistical
Inquiry”, Ph.D. Dissertation, Department of Philosophy, Carnegie
Mellon University,
Genin 2018 available online. (Scholar)
- Genin, K. and Kelly, K., 2015. “Theory Choice, Theory
Change, and Inductive Truth-Conduciveness”, Proceedings of
the 15th Conference on Theoretical Aspects of Rationality and
Knowledge (TARK 2015). Publisher: Electronic Proceedings in
Theoretical Computer Science. Extended Abstract,
Genin & Kelly 2015 available online. (Scholar)
- –––, 2017. “The Topology of Statistical
Verifiability”, Proceedings of the 17th Conference on
Theoretical Aspects of Rationality and Knowledge (TARK 2017).
Electronic Proceedings in Theoretical Computer Science,
preprint available online . (Scholar)
- –––, 2019. “Theory Choice, Theory Change, and Inductive Truth-Conduciveness”, Studia Logica, 107: 949–989. (Scholar)
- Glymour, C., 1991. “The Hierarchies of Knowledge and the Mathematics of Discovery”, Minds and Machines, 1: 75–95. (Scholar)
- –––, 1994. “On the Methods of Cognitive Neuropsychology”, British Journal for the Philosophy of Science, 45: 815–35. (Scholar)
- Glymour, C. and Kelly, K., 1992. “Thoroughly Modern Meno”, in Inference, Explanation and Other Frustrations, John Earman (ed.), Berkeley: University of California Press. (Scholar)
- Gold, E., 1967. “Language Identification in the
Limit”, Information and Control, 10:
447–474. (Scholar)
- Goodman, N., 1983. Fact, Fiction and Forecast, Cambridge, MA: Harvard University Press. (Scholar)
- Harrell, M., 2000. Chaos and Reliable Knowledge, Ph.D. Dissertation, University of California at San Diego. (Scholar)
- Harman, G. and Kulkarni, S., 2007. Reliable Reasoning: Induction and Statistical Learning Theory, Cambridge, MA: The MIT Press. (Scholar)
- Huber, F., 2018. A Logical Introduction to Probability and Induction, Oxford: Oxford University Press. (Scholar)
- Jain, S., et al., 1999. Systems That Learn,
2nd edition, Cambridge, MA: MIT Press. (Scholar)
- James, W., 1982. “The Will To Believe”, in
Pragmatism, H.S. Thayer (ed.), Indianapolis: Hackett. (Scholar)
- Juhl, C., 1997. “Objectively Reliable Subjective
Probabilities”, Synthese, 109: 293–309. (Scholar)
- Kelly, K., 1996. The Logic of Reliable Inquiry, Oxford: Oxford University Press. (Scholar)
- –––, 1999. “ Iterated Belief Revision, Reliability, and Inductive Amnesia”, Erkenntnis, 50: 11–58. (Scholar)
- –––, 2000. “The Logic of Success”, British Journal for the Philosophy of Science, 51(4): 639–660. (Scholar)
- –––, 2007a. “How Simplicity Helps You Find the Truth Without Pointing at it”, in Induction, Algorithmic Learning Theory, and Philosophy, M. Friend, N. Goethe and V. Harazinov (eds.), Dordrecht: Springer, pp. 111–144. (Scholar)
- –––, 2008. ‘Ockham’s Razor, Truth,
and Information’, in Handbook of the Philosophy of
Information, J. van Behthem and P. Adriaans (eds.), Dordrecht:
Elsevier. (Scholar)
- –––, 2010. “Simplicity, Truth, and Probability”, in Handbook for the Philosophy of Statistics, Prasanta S. Bandyopadhyay and Malcolm Forster (eds.), Dordrecht: Elsevier. (Scholar)
- Kelly, K., and Schulte, O., 1995. “The Computable Testability of Theories Making Uncomputable Predictions”, Erkenntnis, 43: 29–66. (Scholar)
- Kelly, K., Schulte, O. and Juhl, C., 1997. “Learning Theory and the Philosophy of Science”, Philosophy of Science, 64: 245–67. (Scholar)
- Kuhn, T., 1970. The Structure of Scientific Revolutions. Chicago: University of Chicago Press. (Scholar)
- Luo, W. and Schulte O., 2006. “Mind Change Efficient Learning”, in Logic and Computation, 204: 989–1011. (Scholar)
- Martin, E. and Osherson, D., 1998. Elements of Scientific Inquiry, Cambridge, MA: MIT Press. (Scholar)
- Ne’eman, Y. and Kirsh, Y., 1983. The Particle
Hunters, Cambridge: Cambridge University Press. (Scholar)
- Omnes, R., 1971. Introduction to Particle Physics,
London, New York: Wiley Interscience. (Scholar)
- Popper, Karl, 1962. Conjectures and refutations. The growth of scientific knowledge, New York: Basic Books. (Scholar)
- Putnam, H., 1963. “Degree of Confirmation and Inductive Logic”, in The Philosophy of Rudolf Carnap, P.A. Schilpp (ed.), La Salle, Ill: Open Court. (Scholar)
- Putnam, H., 1965. “Trial and Error Predicates and the Solution to a Problem of Mostowski”, Journal of Symbolic Logic, 30(1): 49–57. (Scholar)
- Quine, W., 1951. “Two Dogmas of Empiricism”, Philosophical Review, 60: 20–43. (Scholar)
- Salmon, W., 1991. “Hans Reichenbach’s Vindication of
Induction”, Erkenntnis, 35: 99–122. (Scholar)
- Schulte, O., 1999. “Means-Ends Epistemology”, The British Journal for the Philosophy of Science, 50: 1–31. (Scholar)
- –––, 2008. “The Co-Discovery of Conservation Laws and Particle Families”, Studies in History and Philosophy of Modern Physics, 39(2): 288–314. (Scholar)
- –––, 2009. “Simultaneous Discovery of
Conservation Laws and Hidden Particles With Smith Matrix
Decomposition”, in Proceedings of the Twenty-First
International Joint Conference on Artificial Intelligence
(IJCAI-09), Palo Alto: AAAI Press pp. 1481-1487. (Scholar)
- Schulte, O., Luo, W., and Greiner, R., 2007. “Mind Change
Optimal Learning of Bayes Net Structure”, in Proceedings of
the 20th Annual Conference on Learning Theory (COLT’07, San
Diego, CA, June 12–15), N. Bshouti and C. Gentile (eds.),
Berlin, Heidelberg: Springer, pp. 187–202. (Scholar)
- Schulte, O., and Cory Juhl, 1996. “Topology as Epistemology”, The Monist, 79(1): 141–147. (Scholar)
- Sklar, L., 1975. “Methodological Conservatism”, Philosophical Review, 84: 374–400. (Scholar)
- Sober, E., 2015. Ockham’s Razors, Cambridge:
Cambridge University Press. (Scholar)
- Spirtes, P., Glymour, C., Scheines, R., 2000. Causation,
prediction, and search, Cambridge, MA: MIT Press. (Scholar)
- Steel, D., 2009. “Testability and Ockham’s Razor: How
Formal and Statistical Learning Theory Converge in the New Riddle of
Induction,” Journal of Philosophical Logic, 38:
471–489. (Scholar)
- –––, 2010. “What if the principle of induction is normative? Formal learning theory and Hume’s problem”, International Studies in the Philosophy of Science, 24(2): 171–185. (Scholar)
- Valiant, L. G., 1984. “A theory of the learnable”,
Proceedings of the Sixteenth Annual ACM Symposium on Theory of
Computing (STOC 84), New York: ACM Press, pp. 436–445.
- Vickers, S., 1996. Topology Via Logic, Cambridge:
Cambridge University Press. (Scholar)