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Organic Computing and Swarm Intelligence

  • Daniel Merkle
  • Martin Middendorf
  • Alexander Scheidler
Part of the Natural Computing Series book series (NCS)

Abstract

The relations between swarm intelligence and organic computing are discussed in this chapter. The aim of organic computing is to design and study computing systems that consist of many autonomous components and show forms of collective behavior. Such organic computing systems (OC systems) should possess self-x properties (e.g., self-healing, self-managing, self-optimizing), have a decentralized control, and be adaptive to changing requirements of their user. Examples of OC systems are described in this chapter and two case studies are presented that show in detail that OC systems share important properties with social insect colonies and how methods of swarm intelligence can be used to solve problems in organic computing.

Keywords

Swarm Intelligence Simulation Step Emergent Behavior Cluster Agent Speed Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Daniel Merkle
    • 1
  • Martin Middendorf
    • 1
  • Alexander Scheidler
    • 1
  1. 1.Department of Computer ScienceUniversity of LeipzigLeipzigGermany

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