Analysis and Design of Machine Learning Techniques Evolutionary

Manipulating or grasping objects seems like a trivial task for humans, as these are motor skills of everyday life. Nevertheless, motor skills are not easy to learn for humans and this is also an active research topic in robotics. However, most solutions a

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Patrick Stalph

Analysis and Design of Machine Learning Techniques Evolutionary Solutions for Regression, Prediction, and Control Problems

Patrick Stalph Tübingen, Germany

PhD Thesis, University of Tübingen, 2013

ISBN 978-3-658-04936-2 DOI 10.1007/978-3-658-04937-9

ISBN 978-3-658-04937-9 (eBook)

The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available in the Internet at http://dnb.d-nb.de. Library of Congress Control Number: 2014931388 Springer Vieweg © Springer Fachmedien Wiesbaden 2014 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Springer Vieweg is a brand of Springer DE. Springer DE is part of Springer Science+Business Media. www.springer-vieweg.de

Acknowledgments First, I’d like to thank my supervisor, Martin Butz, for his support in general and, particularly, his constructive criticism, when it came to scientific writing. Furthermore, I want to thank the members of the department of cognitive modelling, formerly called COBOSLAB, for all those inspiring discussions. I also want to thank Moritz Str¨ ube, David Hock, Andreas Alin, Stephan Ehrenfeld, and Jan Kneissler for helpful reviews. Most importantly, I’m grateful for my wife being so patient with me. Patrick Stalph

Abstract Manipulating or grasping objects seems like a trivial task for hum