Overview
- Captures the most representative approaches of the emerging field of guided self-organization, and covers its development over the last few years
- Includes in-depth reviews and descriptions of future research in the most important guided self-organization areas
- Offers a comprehensive perspective on guided self-organization at the early years of this emerging field
- Edited and written by leading experts in the field
Part of the book series: Emergence, Complexity and Computation (ECC, volume 9)
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Table of contents (16 chapters)
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Front Matter
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Introduction
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Front Matter
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Foundational Frameworks
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Front Matter
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Coordinated Behaviour and Learning within an Embodied Agent
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Front Matter
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Swarms and Networks of Agents
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Front Matter
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Keywords
About this book
Is it possible to guide the process of self-organisation towards specific patterns and outcomes? Wouldn’t this be self-contradictory? After all, a self-organising process assumes a transition into a more organised form, or towards a more structured functionality, in the absence of centralised control. Then how can we place the guiding elements so that they do not override rich choices potentially discoverable by an uncontrolled process?
This book presents different approaches to resolving this paradox. In doing so, the presented studies address a broad range of phenomena, ranging from autopoietic systems to morphological computation, and from small-world networks to information cascades in swarms. A large variety of methods is employed, from spontaneous symmetry breaking to information dynamics to evolutionary algorithms, creating a rich spectrum reflecting this emerging field.
Demonstrating several foundational theories and frameworks, as well as innovative practical implementations, Guided Self-Organisation: Inception, will be an invaluable tool for advanced students and researchers in a multiplicity of fields across computer science, physics and biology, including information theory, robotics, dynamical systems, graph theory, artificial life, multi-agent systems, theory of computation and machine learning.
Editors and Affiliations
Bibliographic Information
Book Title: Guided Self-Organization: Inception
Editors: Mikhail Prokopenko
Series Title: Emergence, Complexity and Computation
DOI: https://doi.org/10.1007/978-3-642-53734-9
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2014
Hardcover ISBN: 978-3-642-53733-2Published: 09 January 2014
Softcover ISBN: 978-3-662-52392-6Published: 27 September 2016
eBook ISBN: 978-3-642-53734-9Published: 19 December 2013
Series ISSN: 2194-7287
Series E-ISSN: 2194-7295
Edition Number: 1
Number of Pages: XXII, 475
Number of Illustrations: 118 b/w illustrations, 54 illustrations in colour
Topics: Complexity, Theory of Computation, Artificial Intelligence, Computational Intelligence, Applications of Nonlinear Dynamics and Chaos Theory