Probability Collectives A Distributed Multi-agent System Approach fo
This book provides an emerging computational intelligence tool in the framework of collective intelligence for modeling and controlling distributed multi-agent systems referred to as Probability Collectives. In the modified Probability Collectives methodo
- PDF / 6,575,861 Bytes
- 162 Pages / 453.543 x 683.15 pts Page_size
- 39 Downloads / 182 Views
Anand Jayant Kulkarni Kang Tai Ajith Abraham
Probability Collectives A Distributed Multi-agent System Approach for Optimization
Intelligent Systems Reference Library Volume 86
Series editors Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland e-mail: [email protected] Lakhmi C. Jain, University of Canberra, Canberra, Australia, and University of South Australia, Adelaide, Australia e-mail: [email protected]
About this Series The aim of this series is to publish a Reference Library, including novel advances and developments in all aspects of Intelligent Systems in an easily accessible and well structured form. The series includes reference works, handbooks, compendia, textbooks, well-structured monographs, dictionaries, and encyclopedias. It contains well integrated knowledge and current information in the field of Intelligent Systems. The series covers the theory, applications, and design methods of Intelligent Systems. Virtually all disciplines such as engineering, computer science, avionics, business, e-commerce, environment, healthcare, physics and life science are included.
More information about this series at http://www.springer.com/series/8578
Anand Jayant Kulkarni Kang Tai Ajith Abraham •
•
Probability Collectives A Distributed Multi-agent System Approach for Optimization
123
Anand Jayant Kulkarni School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore Singapore
Ajith Abraham Scientific Network for Innovation and Research Excellence Machine Intelligence Research Labs (MIR Labs) Auburn, WA USA
Kang Tai School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore Singapore
ISSN 1868-4394 ISSN 1868-4408 (electronic) Intelligent Systems Reference Library ISBN 978-3-319-15999-7 ISBN 978-3-319-16000-9 (eBook) DOI 10.1007/978-3-319-16000-9 Library of Congress Control Number: 2015932843 Springer Cham Heidelberg New York Dordrecht London © Springer International Publishing Switzerland 2015 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. 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. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained he
Data Loading...