• DocumentCode
    3398462
  • Title

    Visualizing the loss of diversity in genetic programming

  • Author

    Daida, J.M. ; Ward, David J. ; Hilss, Adam M. ; Long, Stephen L. ; Hodges, Mark R. ; Kriesel, Jason T.

  • Author_Institution
    Center for the Study of Complex Syst. & Space Phys. Res. Lab., Ann Arbor, MI, USA
  • Volume
    2
  • fYear
    2004
  • fDate
    19-23 June 2004
  • Firstpage
    1225
  • Abstract
    This work introduces visualization techniques that allow for a multivariate approach in understanding the dynamics that underlie genetic programming (GP). Emphasis is given toward understanding the relationship between problem difficulty and the loss of diversity. The visualizations raise questions about diversity and problem solving efficacy, as well as the role of the initial population in determining solution outcomes.
  • Keywords
    data visualisation; genetic algorithms; genetic programming; initial population; problem solving efficacy; visualization techniques; Convergence; Data visualization; Dynamic programming; Evolutionary computation; Genetic programming; Laboratories; Particle measurements; Problem-solving; Robustness; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2004. CEC2004. Congress on
  • Print_ISBN
    0-7803-8515-2
  • Type

    conf

  • DOI
    10.1109/CEC.2004.1331037
  • Filename
    1331037