Unified Computational Intelligence for Complex Systems
Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained,
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Adaptation, Learning, and Optimization, Volume 6 Series Editor-in-Chief Meng-Hiot Lim Nanyang Technological University, Singapore E-mail: [email protected] Yew-Soon Ong Nanyang Technological University, Singapore E-mail: [email protected] Further volumes of this series can be found on our homepage: springer.com Vol. 1. Jingqiao Zhang and Arthur C. Sanderson Adaptive Differential Evolution, 2009 ISBN 978-3-642-01526-7 Vol. 2. Yoel Tenne and Chi-Keong Goh (Eds.) Computational Intelligence in Expensive Optimization Problems, 2010 ISBN 978-3-642-10700-9 Vol. 3. Ying-ping Chen (Ed.) Exploitation of Linkage Learning in Evolutionary Algorithms, 2010 ISBN 978-3-642-12833-2 Vol. 4. Anyong Qing and Ching Kwang Lee Differential Evolution in Electromagnetics, 2010 ISBN 978-3-642-12868-4 Vol. 5. Ruhul A. Sarker and Tapabrata Ray (Eds.) Agent-Based Evolutionary Search, 2010 ISBN 978-3-642-13424-1 Vol. 6. John Seiffertt and Donald C. Wunsch Unified Computational Intelligence for Complex Systems, 2010 ISBN 978-3-642-03179-3
John Seiffertt and Donald C. Wunsch
Unified Computational Intelligence for Complex Systems
123
John Seiffertt PhD Candidate Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla, MO 65402 USA E-mail: [email protected]
Dr. Donald Wunsch Mark K Finley Missouri Distinguished Professor Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla, MO 65402 USA E-mail: [email protected]
ISBN 978-3-642-03179-3
e-ISBN 978-3-642-03180-9
DOI 10.1007/978-3-642-03180-9 Adaptation, Learning, and Optimization
ISSN 1867-4534
Library of Congress Control Number: 2010928723 c 2010 Springer-Verlag Berlin Heidelberg
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Contents
Contents 1
Introduction………………………………………………………………....1 1.1 The Need for Unified Computational Intelligence..................................1 1.2 Contributions of This Work....................................................................4 1.3 The Three Types of Machine Learning ..................................................4 1.3.1 Unsupervised L
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