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Extending Particle Swarm Optimisation via Genetic Programming

  • Riccardo Poli
  • William B. Langdon
  • Owen Holland
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3447)

Abstract

Particle Swarm Optimisers (PSOs) search using a set of interacting particles flying over the fitness landscape. These are typically controlled by forces that encourage each particle to fly back both towards the best point sampled by it and towards the swarm’s best. Here we explore the possibility of evolving optimal force generating equations to control the particles in a PSO using genetic programming.

Keywords

Particle Swarm Optimisation Global Optimum Particle Swarm Genetic Programming Swarm 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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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Riccardo Poli
    • 1
  • William B. Langdon
    • 1
  • Owen Holland
    • 1
  1. 1.Department of Computer ScienceUniversity of EssexUK

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