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Swarm Intelligence [electronic resource] : Introduction and Applications / edited by Christian Blum, Daniel Merkle.

Contributor(s): Series: Natural Computing SeriesPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008Description: X, 286 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540740896
Subject(s): Genre/Form: Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TJ210.2-211.495
Online resources:
Contents:
Biological Foundations of Swarm Intelligence -- Swarm Intelligence in Optimization -- Swarm Robotics -- Routing Protocols for Next-Generation Networks Inspired by Collective Behaviors of Insect Societies: An Overview -- Applications -- Evolution, Self-organization and Swarm Robotics -- Particle Swarms for Dynamic Optimization Problems -- An Agent-Based Approach to Self-organized Production -- Organic Computing and Swarm Intelligence.
In: Springer eBooksSummary: The laws that govern the collective behavior of social insects, flocks of birds, or fish schools continue to mesmerize researchers. While individuals are rather unsophisticated, in cooperation they can solve complex tasks, a prime example being the ability of ant colonies to find shortest paths between their nests and food sources. Task-solving results from self-organization, which often evolves from simple means of communication, either directly or indirectly via changing the environment, the latter referred to as stigmergy. Scientists have applied these principles in new approaches, for example to optimization and the control of robots. Characteristics of the resulting systems include robustness and flexibility. This field of research is now referred to as swarm intelligence. The contributing authors are among the top researchers in their domain. The book is intended to provide an overview of swarm intelligence to novices, and to offer researchers in the field an update on interesting recent developments. Introductory chapters deal with the biological foundations, optimization, swarm robotics, and applications in new-generation telecommunication networks, while the second part contains chapters on more specific topics of swarm intelligence research such as the evolution of robot behavior, the use of particle swarms for dynamic optimization, and organic computing.
Item type: eBooks
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Biological Foundations of Swarm Intelligence -- Swarm Intelligence in Optimization -- Swarm Robotics -- Routing Protocols for Next-Generation Networks Inspired by Collective Behaviors of Insect Societies: An Overview -- Applications -- Evolution, Self-organization and Swarm Robotics -- Particle Swarms for Dynamic Optimization Problems -- An Agent-Based Approach to Self-organized Production -- Organic Computing and Swarm Intelligence.

The laws that govern the collective behavior of social insects, flocks of birds, or fish schools continue to mesmerize researchers. While individuals are rather unsophisticated, in cooperation they can solve complex tasks, a prime example being the ability of ant colonies to find shortest paths between their nests and food sources. Task-solving results from self-organization, which often evolves from simple means of communication, either directly or indirectly via changing the environment, the latter referred to as stigmergy. Scientists have applied these principles in new approaches, for example to optimization and the control of robots. Characteristics of the resulting systems include robustness and flexibility. This field of research is now referred to as swarm intelligence. The contributing authors are among the top researchers in their domain. The book is intended to provide an overview of swarm intelligence to novices, and to offer researchers in the field an update on interesting recent developments. Introductory chapters deal with the biological foundations, optimization, swarm robotics, and applications in new-generation telecommunication networks, while the second part contains chapters on more specific topics of swarm intelligence research such as the evolution of robot behavior, the use of particle swarms for dynamic optimization, and organic computing.

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