Multistrategy Learning - A Special Issue of MACHINE LEARNING (Hardcover, Reprinted from MACHINE LEARNING, 11:2-3, 1993)

Most machine learning research has been concerned with the development of systems that implememnt one type of inference within a single representational paradigm. Such systems, which can be called monostrategy learning systems, include those for empirical induction of decision trees or rules, explanation-based generalization, neural net learning from examples, genetic algorithm-based learning, and others. Monostrategy learning systems can be very effective and useful if learning problems to which they are applied are sufficiently narrowly defined. Many real-world applications, however, pose learning problems that go beyond the capability of monostrategy learning methods. In view of this, recent years have witnessed a growing interest in developing multistrategy systems, which integrate two or more inference types and/or paradigms within one learning system. Such multistrategy systems take advantage of the complementarity of different inference types or representational mechanisms. Therefore, they have a potential to be more versatile and more powerful than monostrategy systems. On the other hand, due to their greater complexity, their development is significantly more difficult and represents a new great challenge to the machine learning community. Multistrategy Learning contains contributions characteristic of the current research in this area.

General

Imprint:	Springer
Country of origin:	Netherlands
Series:	The Springer International Series in Engineering and Computer Science, 240
Release date:	June 1993
First published:	1993
Editors:	Ryszard S. Michalski
Dimensions:	235 x 155 x 11mm (L x W x T)
Format:	Hardcover
Pages:	155
Edition:	Reprinted from MACHINE LEARNING, 11:2-3, 1993
ISBN-13:	978-0-7923-9374-0
Categories:	Books > Reference & Interdisciplinary > Communication studies > Information theory > Cybernetics & systems theory Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	0-7923-9374-0
Barcode:	9780792393740

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