Swarm Intelligence

Introduction and Applications

By Christian Blum , Daniel Merkle

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  • ISBN13: 978-3-5407-4088-9
  • 292 Pages
  • User Level: Science
  • Publication Date: September 24, 2008
  • Available eBook Formats: PDF

Related Titles

  • Information Systems and Neuroscience
Full Description
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.
Table of Contents

Table of Contents

  1. Biological Foundations of Swarm Intelligence.
  2. Swarm Intelligence in Optimization.
  3. Swarm Robotics.
  4. Routing Protocols for Next
  5. Generation Intelligent Networks Inspired by Collective Behaviors of Insect Societies.
  6. Evolution, Self
  7. organization and Swarm Robotics.
  8. Particle Swarms for Dynamic Optimization Problems.
  9. An Agent
  10. Based Approach to Self
  11. organized Production.
  12. Organic Computing and Swarm Intelligence

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