Swarm Stability and Optimization
Swarming species such as flocks of birds or schools of fish exhibit fascinating collective behaviors during migration and predator avoidance. Similarly, engineered multi-agent dynamic systems such as groups of autonomous ground, underwater, or air v
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Veysel Gazi and Kevin M. Passino
Swarm Stability and Optimization
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Authors Dr. Veysel Gazi Firuzkoy Mahallesi, Dervis Sokak No: 10, Avcilar, Istanbul, Turkey E-mail: [email protected] Prof. Kevin Michael Passino The Ohio State University Department of Electrical and Computer Engineering 416 Dreese Laboratories 2015 Neil Ave Columbus, OH 43210 USA E-mail: [email protected]
ISBN 978-3-642-18040-8
e-ISBN 978-3-642-18041-5
DOI 10.1007/978-3-642-18041-5 c Springer Science + Business Media B.V. 2011 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, 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. Typesetting: Data supplied by the authors Cover Design: Scientific Publishing Services Pvt. Ltd., Chennai, India Printed on acid-free paper 987654321 springer.com
To our parents ...
Preface
The beautiful and exotic collective behaviors of swarming species such as some bacteria, ant colonies, bee colonies, flocks of birds, schools of fish, and others, have fascinated and attracted the interest of researchers for many years. Collaborative swarming behavior that we observe in these groups provides survival advantages. The behavior results in what is sometimes called “collective intelligence” or “swarm intelligence” where groups of relatively simple and “unintelligent” individuals can accomplish very complex tasks using only limited local information and simple rules of behavior (e.g., coordinated group motion for predator avoidance). With the development of technology, including the technology on sensing, computation, information processing, power storage and others, it has become feasible to develop engineered autonomous multi-agent dynamic systems such as systems composed of multiple robots, satellites, or ground, air, surface, underwater or deep space vehicles (i.e., “vehicle swarms”). The studies on the dynamics and mechanisms of the behavior of swarms in nature can provide guidelines for developing principles for decentralized and cooperative coordination and control algorithms for engineering multi-agent dynamic systems. In other words, we can learn from the swarms in nature and utilize the resulting concepts and ideas in developing artificial engineering swarms (e.g., for vehicle swarms). This is the focus of this book.
Overview of the Book In this book we have taken a syst
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