Machine Learning: A Multistrategy Approach, Volume IV

by Ryszard S. Michalski, George Tecuci

Overview

Multistrategy learning is one of the newest and most promising research directions in the development of machine learning systems. The objectives of research in this area are to study trade-offs between different learning strategies and to develop learning systems that employ multiple types of inference or computational paradigms in a learning process. Multistrategy systems offer significant advantages over monostrategy systems. They are more flexible in the type of input they can learn from and the type of knowledge they can acquire. As a consequence, multistrategy systems have the potential to be applicable to a wide range of practical problems. This volume is the first book in this fast growing field. It contains a selection of contributions by leading researchers specializing in this area.

Product Details

ISBN-13:	9781558602519
Publisher:	Elsevier Science
Publication date:	02/09/1994
Series:	Machine Learning Series , #4
Edition description:	New Edition
Pages:	782
Product dimensions:	1.69(w) x 6.00(h) x 9.00(d)

Table of Contents

Part One General Issues
Part Two Theory Revision
Part Three Cooperative Integration
Part Four Symbolic and Subsymbolic Learning
Part Five Special Topics and Applications