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

Por: Colaborador(es): Tipo de material: TextoTextoEditor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Descripción: XVII, 299 p. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9783642180415
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 006.3 23
Clasificación LoC:
  • Q342
Recursos en línea:
Contenidos:
Springer eBooksResumen: 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 (ǣvehicle swarmsǥ) 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 (ǣvehicle swarmsǥ) 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.

ZDB-2-ENG

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