• DocumentCode
    1634967
  • Title

    Neutrality and ruggedness in robot landscapes

  • Author

    Smith, Tom ; Philippides, Andy ; Husbands, Phil ; O´Shea, Michael

  • Author_Institution
    Centre for Computational Neurosci. & Robotics (CCNR), Sussex Univ., Brighton, UK
  • Volume
    2
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    1348
  • Lastpage
    1353
  • Abstract
    The twin fitness landscape properties of neutrality and ruggedness are crucial to the dynamics of evolutionary optimisation. In this paper, we investigate the interplay between these two properties in a complex evolutionary robotics fitness landscape, through the introduction of four robot controller architecture models; the GasNet, uniform, dispersed and plexus models. We show that, in isolation, neither added neutrality or decreased ruggedness (coupling) in the models produces increase in the speed of evolution. However, both effects in conjunction produce a significant increase in the speed of evolution
  • Keywords
    evolutionary computation; intelligent control; neural net architecture; neurocontrollers; optimal control; robots; GasNet model; dispersed model; dynamics; evolution rate; evolutionary optimisation; evolutionary robotics; model coupling; neutrality; plexus model; robot controller architecture models; robot fitness landscapes; ruggedness; uniform model; Artificial neural networks; Genetics; Orbital robotics; Organisms; Robot control; Robust stability; Robustness; Signal design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-7282-4
  • Type

    conf

  • DOI
    10.1109/CEC.2002.1004439
  • Filename
    1004439