© 2008

Evolutionary Swarm Robotics

Evolving Self-Organising Behaviours in Groups of Autonomous Robots


  • Presents the concept and recent results in evolutionary swarm robotics


Part of the Studies in Computational Intelligence book series (SCI, volume 108)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. The Evolution of Self-Organization

  3. Experiments with Simulated and Real Robots

  4. Future Directions

  5. Back Matter
    Pages 173-189

About this book


In this book the use of ER techniques for the design of self-organising group behaviours, for both simulated and real robots is introduced. This research has a twofold value. From an engineering perspective, an automatic methodology for synthesising complex behaviours in a robotic system is described.

ER techniques should be used in order to obtain robust and efficient group behaviours based on self-organisation. From a more theoretical point of view, the second important contribution brought forth by the author's experiments concerns the understanding of the basic principles underlying self-organising behaviours and collective intelligence. In this experimental work, the evolved behaviours are analysed in order to uncover the mechanisms that have led to a certain organisation.

In summary, this book tries to mediate between two apparently opposed perspectives: engineering and cognitive science. The experiments presented and the results obtained contribute to the assessment of ER not only as a design tool, but also as a methodology for modelling and understanding intelligent adaptive behaviours.


Computational Intelligence Evolutionary Intelligence Swarm Robotics autonom autonomous robot cognitive science intelligence modeling robot robotics

Authors and affiliations

  1. 1.Istituto di Scienze e Tecnologie della Cognizione00185Italy

Bibliographic information

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From the reviews:

“This book is aimed at engineering and cognitive science researchers interested in evolutionary robotics techniques for the design of self-organizing group behaviors.” (IEEE Control Systems Magazine, Vol. 30, June, 2010)