• DocumentCode
    2447412
  • Title

    Reactive planning idioms for multi-scale game AI

  • Author

    Weber, Ben G. ; Mawhorter, Peter ; Mateas, Michael ; Jhala, Arnav

  • Author_Institution
    Expressive Intell. Studio, Univ. of California, Santa Cruz, CA, USA
  • fYear
    2010
  • fDate
    18-21 Aug. 2010
  • Firstpage
    115
  • Lastpage
    122
  • Abstract
    Many modern games provide environments in which agents perform decision making at several levels of granularity. In the domain of real-time strategy games, an effective agent must make high-level strategic decisions while simultaneously controlling individual units in battle. We advocate reactive planning as a powerful technique for building multi-scale game AI and demonstrate that it enables the specification of complex, real-time agents in a unified agent architecture. We present several idioms used to enable authoring of an agent that concurrently pursues strategic and tactical goals, and an agent for playing the real-time strategy game StarCraft that uses these design patterns.
  • Keywords
    artificial intelligence; behavioural sciences computing; computer games; decision making; multi-agent systems; StarCraft; decision making; effective agent; high-level strategic decision; multiscale game AI; reactive planning idiom; real-time strategy game; unified agent architecture; Artificial intelligence; Buildings; Cognition; Context; Games; Planning; Real time systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Games (CIG), 2010 IEEE Symposium on
  • Conference_Location
    Dublin
  • Print_ISBN
    978-1-4244-6295-7
  • Electronic_ISBN
    978-1-4244-6296-4
  • Type

    conf

  • DOI
    10.1109/ITW.2010.5593363
  • Filename
    5593363