Using the Genetic Regulatory Evolving Artificial Networks (GReaNs) Platform for Signal Processing, Animat Control, and A
Building a system that allows for pattern formation and morphogenesis is a first step towards a biologically-inspired developmental-evolutionary approach to generate complex neural networks. In this chapter we present one such system, for Genetic Regulato
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Taras Kowaliw Nicolas Bredeche René Doursat Editors
Growing Adaptive Machines Combining Development and Learning in Artificial Neural Networks
Studies in Computational Intelligence Volume 557
Series editor Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland e-mail: [email protected]
For further volumes: http://www.springer.com/series/7092
About this Series The series ‘‘Studies in Computational Intelligence’’ (SCI) publishes new developments and advances in the various areas of computational intelligence—quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life sciences, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output.
Taras Kowaliw Nicolas Bredeche René Doursat •
Editors
Growing Adaptive Machines Combining Development and Learning in Artificial Neural Networks
123
Editors Taras Kowaliw Institut des Systèmes Complexes de Paris Île-de-France CNRS Paris France
René Doursat School of Biomedical Engineering Drexel University Philadelphia, PA USA
Nicolas Bredeche Institute of Intelligent Systems and Robotics CNRS UMR 7222 Université Pierre et Marie Curie Paris France
ISSN 1860-949X ISSN 1860-9503 (electronic) ISBN 978-3-642-55336-3 ISBN 978-3-642-55337-0 (eBook) DOI 10.1007/978-3-642-55337-0 Springer Heidelberg New York Dordrecht London Library of Congress Control Number: 2014941221 Springer-Verlag Berlin Heidelberg 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 Clearanc
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