Guided self-organization [electronic resource] : inception / Mikhail Prokopenko, editor.
2014
QA76.889
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Title
Guided self-organization [electronic resource] : inception / Mikhail Prokopenko, editor.
ISBN
9783642537349 electronic book
3642537340 electronic book
9783642537332
3642537340 electronic book
9783642537332
Publication Details
Dordrecht : Springer, [2014]
Language
English
Description
1 online resource (488 pages).
Call Number
QA76.889
Dewey Decimal Classification
004.0151
Summary
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.
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Source of Description
Description based on print version record.
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Series
Emergence, complexity and computation.
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Table of Contents
Foundational frameworks
Coordinated behaviour and learning within an embodied agent
Swarms and networks of agents.
Coordinated behaviour and learning within an embodied agent
Swarms and networks of agents.