• DocumentCode
    1638074
  • Title

    Robustness in evolved grid structures

  • Author

    Ashlock, Daniel ; Schonfeld, Justin ; Humphrey, James

  • Author_Institution
    Dept. of Math. & Stat., Univ. of Guelph, Guelph, ON
  • fYear
    2009
  • Firstpage
    1343
  • Lastpage
    1350
  • Abstract
    This study explores the ability of dynamic polyominos to acquire different types of robustness in a variety of environments. A polyomino is a collection of identical squares joined along their sides to form a connected shape. This study introduces a cellular encoding for polyominos that grow in a manner that adapts to environmental obstructions. Fitness evaluation places polyominos in competition to occupy space with each square of a grid occupiable by only a single individual. Evolved polyomino genomes are studied for their robustness to choice of opponent and environment. This study is part of a series studying the evolution of robustness, enlarging the scope of the series to include robustness against choice of opponent and environment. Polyomino fitness is evaluated in monoculture, multiculture, and obstructed environments. It is found that in all cases added time evolving grants a greater degree of robustness than the other possible sources of robustness. When polyomino genomes have been evolved for comparable amounts of time it is found those with competitive fitness evaluation are superior. When the impact of environmental obstructions are considered it is found that being in your home environment grants a competitive advantage, though not as strong of an advantage as added evolution, with a single exception.
  • Keywords
    biology computing; evolutionary computation; cellular encoding; dynamic polyominos; evolved grid structures; evolved polyomino genomes; Bioinformatics; Biological systems; Evolution (biology); Evolutionary computation; Genetic algorithms; Genetic mutations; Genomics; Noise robustness; Protein engineering; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4983100
  • Filename
    4983100