• DocumentCode
    1822462
  • Title

    Intelligent self-learning characters for computer games

  • Author

    Tang, Wen ; Wan, Tao Ruan

  • Author_Institution
    Sch. of Comput. & Math., Univ. of Teeside, Middlesborough, UK
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    51
  • Lastpage
    58
  • Abstract
    In this paper, a novel AI-based animation approach is presented to simulate intelligent self-learning characters for computer games or other interactive virtual reality applications. The complex learning behaviours of the virtual characters are modelled as an evolutionary process so that adaptive AI algorithms such as genetic algorithms have been used to simulate the learning process. The simulation method enables the characters in a computer game environment to have abilities to learn for specific assigned tasks. Its skill for completing the tasks can be developed and evolved through its experiences of performing the tasks. The paper also describes techniques for performance evaluation and optimisation for virtual characters to perform jumping tasks.
  • Keywords
    artificial intelligence; computer animation; computer games; genetic algorithms; unsupervised learning; virtual reality; AI-based animation; computer games; genetic algorithms; intelligent self-learning characters; interactive virtual reality applications; jumping tasks; learning; performance evaluation; virtual characters; Animation; Application software; Artificial intelligence; Computational modeling; Computer simulation; Games; Genetic algorithms; Humans; Learning; Muscles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Eurographics UK Conference, 2002. Proceedings. The 20th
  • Print_ISBN
    0-7695-1518-5
  • Type

    conf

  • DOI
    10.1109/EGUK.2002.1011272
  • Filename
    1011272