Geometric PSO + GP = particle swarm programming

Julian Togelius, Renzo De Nardi, Alberto Moraglio

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of traditional particle swarm optimization (PSO) that applies naturally to both continuous and combinatorial spaces. In this paper we apply GPSO to the space of genetic programs represented as expression trees, uniting the paradigms of genetic programming and particle swarm optimization. The result is a particle swarm flying through the space of genetic programs. We present initial experimental results for our new algorithm.

    Original languageEnglish (US)
    Title of host publication2008 IEEE Congress on Evolutionary Computation, CEC 2008
    Pages3594-3600
    Number of pages7
    DOIs
    StatePublished - 2008
    Event2008 IEEE Congress on Evolutionary Computation, CEC 2008 - Hong Kong, China
    Duration: Jun 1 2008Jun 6 2008

    Publication series

    Name2008 IEEE Congress on Evolutionary Computation, CEC 2008

    Other

    Other2008 IEEE Congress on Evolutionary Computation, CEC 2008
    CountryChina
    CityHong Kong
    Period6/1/086/6/08

    ASJC Scopus subject areas

    • Computational Theory and Mathematics
    • Theoretical Computer Science

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  • Cite this

    Togelius, J., De Nardi, R., & Moraglio, A. (2008). Geometric PSO + GP = particle swarm programming. In 2008 IEEE Congress on Evolutionary Computation, CEC 2008 (pp. 3594-3600). [4631284] (2008 IEEE Congress on Evolutionary Computation, CEC 2008). https://doi.org/10.1109/CEC.2008.4631284