Abstract
Computational Learning Theory is a recently-developed branch of mathematics which provides a framework for the discussion of experiments with learning machines, such as artificial neural networks. The basic ideas of the theory are described, and applied to an experiment involving the comparison of two learning machines. The experiment was devised so that the results could also be compared with those achieved by a human subject, and this comparison raises some interesting questions.
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© 1992 Springer-Verlag London Limited
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Biggs, N.L. (1992). Learning Algorithms — theory and practice. In: Taylor, J.G. (eds) Neural Network Applications. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-2003-2_1
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DOI: https://doi.org/10.1007/978-1-4471-2003-2_1
Publisher Name: Springer, London
Print ISBN: 978-3-540-19772-0
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