• DocumentCode
    1642010
  • Title

    RAMP: A rule-based agent for Ms. Pac-Man

  • Author

    Fitzgerald, Alan ; Congdon, Clare Bates

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Southern Maine, Portland, ME
  • fYear
    2009
  • Firstpage
    2646
  • Lastpage
    2653
  • Abstract
    RAMP is a rule-based agent for playing Ms. Pac-Man according to the rules stipulated in the 2008 World Congress on Computational Intelligence Ms. Pac-Man Competition. During the competition, our highest score was 15,970, outscoring the eleven other entrants in the competition. In runs reported here, RAMP achieves an average score over 10,000 and a high score of 18,560 across 100 runs; the highest score RAMP has achieved to date is 19,000. These are scores that are better than typical human novice players, including the paper authors themselves. The system was designed to have an evolutionary component, however, this was not developed in time for the competition, which instead used hand-coded rules. We have found the process of tuning the rule sets and accompanying parameters to be a time consuming and inexact process that is expected to benefit from an evolutionary computation approach. This paper describes our initial implementation as well as our progress towards adding an evolutionary computation component to enable the agent learn to play the game.
  • Keywords
    computer games; evolutionary computation; learning (artificial intelligence); software agents; Ms Pac-Man; artificial agent learning; evolutionary computation; hand-coded rule; rule-based agent; Computational intelligence; Computer science; Decision making; Evolutionary computation; Feature extraction; Game theory; Humans; USA Councils; Writing;
  • 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.2009.4983274
  • Filename
    4983274