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Physics - Complexity | Guided Self-Organization: Inception

Guided Self-Organization: Inception

Prokopenko, Mikhail (Ed.)

2014, XXII, 475 p. 172 illus., 54 illus. in color.

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  • 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

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.

Content Level » Research

Keywords » Coordinated behavior for embodied agents - Entropy maximization with empowerment - GSO-2012 workshop - Guide self-organized processes - Information cascades in swarms - Information emergence - Local information dynamics - Measures of emergence - Sensorimotor Loop - Swarm Intelligence

Related subjects » Artificial Intelligence - Complexity - Computational Intelligence and Complexity - Statistical Physics & Dynamical Systems - Theoretical Computer Science

Table of contents 

Foundational frameworks.-

Coordinated behaviour and learning within an embodied agent.-

Swarms and networks of agents.

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