Guided Self-Organization: Inception
Language: English
Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg Jan 2014, 2014
Series: Book 7 of 47 - Emergence, Complexity and Computation
- Hardcover
- New
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
AbeBooks seller since January 23, 2017
Condition: New
£ 141.71
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Add to basketItem description from seller
This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 500 pp. Englisch.…
Seller Inventory # 9783642537332
- Title
- Guided Self-Organization: Inception
- Author
- Mikhail Prokopenko
- Publisher
- Springer Berlin Heidelberg, Springer Berlin Heidelberg Jan 2014
- Publication year
- 2014
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 3642537332
- ISBN 13
- 9783642537332
- Item weight
- 910 grams
- Dimensions
- 241x160x33 mm
- Series
- Book 7 of 47: Emergence, Complexity and Computation
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.
"Synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About the title" may belong to another edition of this title.
buchversandmimpf2000
Emtmannsberg, BAYE, Germany
AbeBooks seller since January 23, 2017
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