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.
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Poli, R., Langdon, W.B., Holland, O. (2005). Extending Particle Swarm Optimisation via Genetic Programming. In: Keijzer, M., Tettamanzi, A., Collet, P., van Hemert, J., Tomassini, M. (eds) Genetic Programming. EuroGP 2005. Lecture Notes in Computer Science, vol 3447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31989-4_26
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DOI: https://doi.org/10.1007/978-3-540-31989-4_26
Publisher Name: Springer, Berlin, Heidelberg
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