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Evolutionary Swarm Robotics [electronic resource] :Evolving Self-Organising Behaviours in Groups of Autonomous Robots / by Vito Trianni.

by Trianni, Vito [author.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Computational Intelligence: 108Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.Description: online resource.ISBN: 9783540776123.Subject(s): Engineering | Artificial intelligence | Mathematics | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Control, Robotics, Mechatronics | Artificial Intelligence (incl. Robotics) | Applications of MathematicsDDC classification: 519 Online resources: Click here to access online
Contents:
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: Springer eBooksSummary: 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.
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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.

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