• DocumentCode
    445480
  • Title

    Environmental fitness for sustained population dynamics

  • Author

    Brodu, Nicolas

  • Author_Institution
    Dept. of Comput. Sci. & Software Eng., Concordia Univ., Montreal, Que.
  • Volume
    1
  • fYear
    2005
  • fDate
    5-5 Sept. 2005
  • Firstpage
    343
  • Abstract
    This study introduces an environment in which agents evolve freely, without an explicit fitness function. The evolution is mainly directed by environmental conditions, and their coupling with the agents. The goal consists in identifying preconditions for a sustainable environment allowing diversity. A method is proposed to analyze which configurations lead to rich population dynamics. The system global behavior is then tuned accordingly. Visualization is also a key component of this project: it offers a qualitative understanding of the simulations
  • Keywords
    genetic algorithms; multi-agent systems; predator-prey systems; agent evolution; environmental fitness; explicit fitness function; sustained population dynamics; Artificial intelligence; Computer science; Evolution (biology); Extraterrestrial phenomena; Genetic algorithms; Machine learning; Physics; Reverse engineering; Software engineering; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2005. The 2005 IEEE Congress on
  • Conference_Location
    Edinburgh, Scotland
  • Print_ISBN
    0-7803-9363-5
  • Type

    conf

  • DOI
    10.1109/CEC.2005.1554704
  • Filename
    1554704