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Ideal Learning Machines
Cognitive Science 6 (3):277-290 (1982)
Abstract
We examine the prospects for finding “best possible” or “ideal” computing machines for various learning tasks. For this purpose, several precise senses of “ideal machine” are considered within the context of formal learning theory. Generally negative results are provided concerning the existence of ideal learning‐machines in the senses considered.My notes
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Citations of this work
On the Necessity of U-Shaped Learning.Lorenzo Carlucci & John Case - 2013 - Topics in Cognitive Science 5 (1):56-88.
References found in this work
Theory of recursive functions and effective computability.Hartley Rogers - 1987 - Cambridge, Mass.: MIT Press.
Computability and Logic.George Boolos, John Burgess, Richard P. & C. Jeffrey - 1980 - New York: Cambridge University Press. Edited by John P. Burgess & Richard C. Jeffrey.
Computability and Logic.George S. Boolos, John P. Burgess & Richard C. Jeffrey - 2003 - Bulletin of Symbolic Logic 9 (4):520-521.
Theory of Recursive Functions and Effective Computability.Hartley Rogers - 1971 - Journal of Symbolic Logic 36 (1):141-146.
Learning by creatifying transfer frames.Patrick H. Winston - 1978 - Artificial Intelligence 10 (2):147-172.
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