• DocumentCode
    2416039
  • Title

    Interactively training first person shooter bots

  • Author

    McPartland, Michelle ; Gallagher, Marcus

  • Author_Institution
    Univ. of Queensland, Brisbane, QLD, Australia
  • fYear
    2012
  • fDate
    11-14 Sept. 2012
  • Firstpage
    132
  • Lastpage
    138
  • Abstract
    Interactive training is a technique that allows humans to guide a learning algorithm. This technique is well suited to training first person shooter bots as it allows game designers to iterate a range of behaviors in real-time. This paper investigates an initial attempt at allowing users to interact with the learning process of a reinforcement learning algorithm to create first person shooter bot behaviors. The results clearly show that it is possible to create different types of bot behaviors using the developed interactive training tool.
  • Keywords
    computer games; interactive systems; learning (artificial intelligence); software agents; first person shooter bot behaviors; first person shooter bots; interactive training tool; reinforcement learning algorithm; Games; Humans; Learning systems; Machine learning; Training; Weapons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Games (CIG), 2012 IEEE Conference on
  • Conference_Location
    Granada
  • Print_ISBN
    978-1-4673-1193-9
  • Electronic_ISBN
    978-1-4673-1192-2
  • Type

    conf

  • DOI
    10.1109/CIG.2012.6374149
  • Filename
    6374149