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Swarm Stability and Optimization [electronic resource] / by Veysel Gazi, Kevin M. Passino.

By: Gazi, Veysel [author.].
Contributor(s): Passino, Kevin M [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Description: XVIII, 302p. 74 illus., 60 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642180415.Subject(s): Engineering | Artificial intelligence | Computer vision | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics) | Control, Robotics, Mechatronics | Image Processing and Computer VisionDDC classification: 006.3 Online resources: Click here to access online
Contents:
Part I Basic Principles -- Part II Continuous Time Swarms -- Part III Discrete Time Swarms -- Part IV Swarm Based Optimization Methods.
In: Springer eBooksSummary: Swarming species such as flocks of birds or schools of fish exhibit fascinating collective behaviors during migration and predator avoidance.  Similarly, engineered multi-agent dynamic systems such as groups of autonomous ground, underwater, or air vehicles (“vehicle swarms”) exhibit sophisticated collective behaviors while maneuvering. In this book we show how to model and control a wide range of such multi-agent dynamic systems and analyze their collective behavior using both stability theoretic and simulation-based approaches. In particular, we investigate problems such as group aggregation, social foraging, formation control, swarm tracking, distributed agreement, and engineering optimization inspired by swarm behavior.
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Part I Basic Principles -- Part II Continuous Time Swarms -- Part III Discrete Time Swarms -- Part IV Swarm Based Optimization Methods.

Swarming species such as flocks of birds or schools of fish exhibit fascinating collective behaviors during migration and predator avoidance.  Similarly, engineered multi-agent dynamic systems such as groups of autonomous ground, underwater, or air vehicles (“vehicle swarms”) exhibit sophisticated collective behaviors while maneuvering. In this book we show how to model and control a wide range of such multi-agent dynamic systems and analyze their collective behavior using both stability theoretic and simulation-based approaches. In particular, we investigate problems such as group aggregation, social foraging, formation control, swarm tracking, distributed agreement, and engineering optimization inspired by swarm behavior.

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