Guided Self-Organization: Inception

  • Mikhail Prokopenko

Part of the Emergence, Complexity and Computation book series (ECC, volume 9)

Table of contents

  1. Front Matter
    Pages 1-20
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Mikhail Prokopenko, Daniel Polani, Nihat Ay
      Pages 3-15
  3. Foundational Frameworks

    1. Front Matter
      Pages 17-17
    2. Nelson Fernández, Carlos Maldonado, Carlos Gershenson
      Pages 19-51
    3. Christoph Salge, Cornelius Glackin, Daniel Polani
      Pages 67-114
    4. Joseph T. Lizier, Mikhail Prokopenko, Albert Y. Zomaya
      Pages 115-158
    5. Virgil Griffith, Christof Koch
      Pages 159-190
  4. Coordinated Behaviour and Learning within an Embodied Agent

    1. Front Matter
      Pages 191-191
    2. Georg Martius, Ralf Der, J. Michael Herrmann
      Pages 223-260
    3. Nihat Ay, Keyan Zahedi
      Pages 261-294
    4. Oliver Obst, Joschka Boedecker
      Pages 319-340
  5. Swarms and Networks of Agents

    1. Front Matter
      Pages 341-341
    2. Jennifer M. Miller, X. Rosalind Wang, Joseph T. Lizier, Mikhail Prokopenko, Louis F. Rossi
      Pages 343-364
    3. Valerio Sperati, Vito Trianni, Stefano Nolfi
      Pages 389-414
    4. Larry S. Yaeger
      Pages 415-454

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.


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

Editors and affiliations

  • Mikhail Prokopenko
    • 1
  1. 1.CSIRO ICT CentreEppingAustralia

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2014
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-53733-2
  • Online ISBN 978-3-642-53734-9
  • Series Print ISSN 2194-7287
  • Series Online ISSN 2194-7295
  • About this book