• DocumentCode
    2910118
  • Title

    Evolving diverse Ms. Pac-Man playing agents using genetic programming

  • Author

    Alhejali, Atif M. ; Lucas, Simon M.

  • Author_Institution
    Game Intell. Group, Univ. of Essex, Colchester, UK
  • fYear
    2010
  • fDate
    8-10 Sept. 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper uses genetic programming (GP) to evolve a variety of reactive agents for a simulated version of the classic arcade game Ms. Pac-Man. A diverse set of behaviours were evolved using the same GP setup in three different versions of the game. The results show that GP is able to evolve controllers that are well-matched to the game used for evolution and, in some cases, also generalise well to previously unseen mazes. For comparison purposes, we also designed a controller manually using the same function set as GP. GP was able to significantly outperform this hand-designed controller. The best evolved controllers are competitive with the best reactive controllers reported for this problem.
  • Keywords
    computer games; genetic algorithms; learning (artificial intelligence); software agents; Ms PacMan game; genetic programming; reactive agents; Artificial intelligence; Artificial neural networks; Games; Genetic programming; Humans; Safety; Testing; Evolving Controllers; Genetic Programming; Pac-Man;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence (UKCI), 2010 UK Workshop on
  • Conference_Location
    Colchester
  • Print_ISBN
    978-1-4244-8774-5
  • Electronic_ISBN
    978-1-4244-8773-8
  • Type

    conf

  • DOI
    10.1109/UKCI.2010.5625586
  • Filename
    5625586