• DocumentCode
    2466278
  • Title

    Evolving expert agent parameters for capture the flag agent in Xpilot

  • Author

    Parker, Gary ; Penrose, Sarah

  • Author_Institution
    Dept. of Comput. Sci., Connecticut Coll., New London, CT, USA
  • fYear
    2012
  • fDate
    14-17 Oct. 2012
  • Firstpage
    791
  • Lastpage
    796
  • Abstract
    Xpilot is an open source, 2d space combat game. Xpilot-AI allows a programmer to write scripts that control an agent playing a game of Xpilot. It provides a reasonable environment for testing learning systems for autonomous agents, both video game agents and robots. In previous work, a wide range of techniques have been used to develop controllers that are focused on the combat skills for an Xpilot agent. In this research, a Genetic Algorithm (GA) was used to evolve the parameters for an expert agent solving the more challenging problem of capture the flag.
  • Keywords
    computer games; genetic algorithms; learning (artificial intelligence); multi-agent systems; public domain software; GA; Xpilot agent; Xpilot-AI; autonomous agents; combat skills; evolving expert agent parameters; flag capture agent; genetic algorithm; learning systems; open source 2d space combat game; robots; video game agents; Biological cells; Games; Genetic algorithms; Marine vehicles; Radar; Sociology; Statistics; Xpilot-AI; autonomous agent; evolutionary computation; genetic algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4673-1713-9
  • Electronic_ISBN
    978-1-4673-1712-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2012.6377824
  • Filename
    6377824