Multistrategy Learning
Subtitle: a Special Issue of MACHINE LEARNING
By: edited by Ryszard S. Michalski
Series: The Springer International Series in Engineering and Computer Science, Knowledge Representation, Learning and Expert Systems -- 240; Springer International Series in Engineering and Computer Science, Knowledge Representation, Learning and Expert Systems -- 240.
Publisher: Springer US
Published: 1993
Place of publication: Boston, MA
Language: eng
Format: [electronic resource] :
Number of pages: 155
ISBN-13: 9781461364054; 9781461532026
Subjects: Computer science; Artificial intelligence
Description: 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.
Notes: Online full text is restricted to subscribers.

Also available in print.

Mode of access: World Wide Web.