Author: Petsche, Thomas (Editor)
Title: Computational Learning Theory and Natural Learning Systems, Vol. II: Intersections between Theory and Experiment.
Description: Cambridge, MA: The MIT Press, 1994. Paperback. 584 pp.- As with Volume I, this second volume represents a synthesis of issues in three historically distinct areas of learning research: computational learning theory, neural network research, and symbolic machine learning. While the first volume provided a forum for building a science of computational learning across fields, this volume attempts to define plausible areas of joint research: the contributions are concerned with finding constraints for theory while at the same time interpreting theoretic results in the context of experiments with actual learning systems. Subsequent volumes will focus on areas identified as research opportunities. Computational learning theory, neural networks, and AI machine learning appear to be disparate fields; in fact they have the same goal: to build a machine or program that can learn from its environment. Accordingly, many of the papers in this volume deal with the problem of learning from examples. In particular, they are intended to encourage discussion between those trying to build learning algorithms (for instance, algorithms addressed by learning theoretic analyses are quite different from those used by neural network or machine-learning researchers) and those trying to analyze them. English text. Condition : as new. Mailorder only - Alleen verzending mogelijk. Book condition : as new. ISBN 9780262581332.

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