• DocumentCode
    2983232
  • Title

    Evolvability in Evolutionary Robotics: Evolving the Genotype-Phenotype Mapping

  • Author

    Koenig, Lionel ; Schmeck, Hartmut

  • Author_Institution
    Inst. AIFB, Karlsruhe Inst. of Technol., Karlsruhe, Germany
  • fYear
    2010
  • fDate
    Sept. 27 2010-Oct. 1 2010
  • Firstpage
    259
  • Lastpage
    260
  • Abstract
    A completely evolvable genotype-phenotype mapping (ceGPM) is studied with respect to its capability of improving the flexibility of artificial evolution. By letting mutation affect not only controller genotypes, but also the mapping from genotype to phenotype, the future e effects of mutation can change over time. In this way, the need for prior parameter adaptation can be reduced. Experiments indicate that the ceGPM is capable of robustly adapting to a benchmark behavior. A comparison to a related approach shows significant improvements in evolvability.
  • Keywords
    artificial life; evolutionary computation; multi-robot systems; self-adjusting systems; artificial evolution; evolutionary robotics; genotype-phenotype mapping; mutation affect; parameter adaptation; Aerospace electronics; Automata; Bars; Mobile robots; Robot sensing systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Self-Adaptive and Self-Organizing Systems (SASO), 2010 4th IEEE International Conference on
  • Conference_Location
    Budapest
  • Print_ISBN
    978-1-4244-8537-6
  • Electronic_ISBN
    978-0-7695-4232-4
  • Type

    conf

  • DOI
    10.1109/SASO.2010.27
  • Filename
    5630047