Evolutionary computation variants for cooperative spatial coordination

G. Yannakakis, J.M. Levine, J. Hallam

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

This paper presents a comparative study between genetic and probabilistic search approaches of evolutionary computation. They are both applied for optimizing the behavior of multiple neural-controlled homogeneous agents whose spatial coordination tasks can only be successfully achieved through emergent cooperation. Both approaches demonstrate effective solutions of high performance; however, the genetic search approach appears to be both more robust and computationally preferred for this multi-agent case study.
Original languageEnglish
Title of host publicationProceedings of the 2005 IEEE Congress on Evolutionary Computation
PublisherIEEE
Pages2715-2722
Number of pages7
Volume3
ISBN (Print)0-7803-9363-5
DOIs
Publication statusPublished - Sep 2005

Keywords

  • evolutionary computation
  • genetic algorithms
  • multi-agent systems
  • search problems

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  • Cite this

    Yannakakis, G., Levine, J. M., & Hallam, J. (2005). Evolutionary computation variants for cooperative spatial coordination. In Proceedings of the 2005 IEEE Congress on Evolutionary Computation (Vol. 3, pp. 2715-2722). IEEE. https://doi.org/10.1109/CEC.2005.1555035