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Maturity of the Particle Swarm as a Metric for Measuring the Collective Intelligence of the Swarm

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7928)

Abstract

The particle swarm collective intelligence has been recognized as a tool for dealing with the optimization of multimodal functions with many local optima. In this article, a research work is introduced in which the cooperative Particle Swarm Optimization strategies are analysed and the collective intelligence of the particle swarm is assessed according to the proposed Maturity Model. The model is derived from the Maturity Model of C2 (Command and Control) operational space and the model of Collaborating Software. The aim was to gain a more thorough explanation of how the intelligent behaviour of the particle swarm emerges. It has been concluded that the swarm system is not mature enough because of the lack of the system’s awareness, and that a solution would be some adaptation of particle’s behavioural rules so that the particle could adjust its velocity using control parameters whose value would be derived from inside of the swarm system, without tuning.

Keywords

  • Particle Swarm Optimizer
  • Particle Swarm
  • Particle Swarm Optimizer Algorithm
  • Inertia Weight
  • Collective Intelligence

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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Winklerová, Z. (2013). Maturity of the Particle Swarm as a Metric for Measuring the Collective Intelligence of the Swarm. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38703-6_5

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  • DOI: https://doi.org/10.1007/978-3-642-38703-6_5

  • Publisher Name: Springer, Berlin, Heidelberg

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