Table of contents
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
- Book Title Guided Self-Organization: Inception
- Series Title Emergence, Complexity and Computation
- Series Abbreviated Title Emergence, Complexity, Computation
- DOI https://doi.org/10.1007/978-3-642-53734-9
- Copyright Information Springer-Verlag Berlin Heidelberg 2014
- Publisher Name Springer, Berlin, Heidelberg
- eBook Packages Engineering Engineering (R0)
- Hardcover ISBN 978-3-642-53733-2
- Softcover ISBN 978-3-662-52392-6
- eBook ISBN 978-3-642-53734-9
- 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
Theory of Computation
Applications of Nonlinear Dynamics and Chaos Theory
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