Evolutionary Swarm Robotics [electronic resource] : Evolving Self-Organising Behaviours in Groups of Autonomous Robots / by Vito Trianni.
Tipo de material: TextoSeries Studies in Computational Intelligence ; 108 | Studies in Computational Intelligence ; 108Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008Descripción: XVI, 192 p. online resourceTipo de contenido:- text
- computer
- online resource
- 9783540776123
- SpringerLink (Online service)
- 519 23
- TA329-348
- TA640-643
The Evolution of Self-Organization -- Embodied Cognitive Science -- Multi-Robot Systems, Swarm Robotics and Self-Organisation -- Evolutionary Robotics for Self-Organising Behaviours -- Experiments with Simulated and Real Robots -- A Self-Organising Artefact: The Swarm-bot -- Coordinated Motion -- Hole Avoidance -- Self-Organising Synchronisation -- Future Directions -- Emergent Collective Decisions through Self-Organisation -- Decision-Making Mechanisms through the Perception of Time -- From Solitary to Collective Behaviours: Decision Making and Cooperation -- Conclusions.
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.
ZDB-2-ENG
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