• DocumentCode
    2716006
  • Title

    Evolving Players for an Ancient Game: Hnefatafl

  • Author

    Hingston, Philip

  • Author_Institution
    Sch. of Comput. & Inf. Sci., Edith Cowan Univ., Churchlands, WA
  • fYear
    2007
  • fDate
    1-5 April 2007
  • Firstpage
    168
  • Lastpage
    174
  • Abstract
    Hnefatafl is an ancient Norse game - an ancestor of chess. In this paper, we report on the development of computer players for this game. In the spirit of Blondie24, we evolve neural networks as board evaluation functions for different versions of the game. An unusual aspect of this game is that there is no general agreement on the rules: it is no longer much played, and game historians attempt to infer the rules from scraps of historical texts, with ambiguities often resolved on gut feeling as to what the rules must have been in order to achieve a balanced game. We offer the evolutionary method as a means by which to judge the merits of alternative rule sets
  • Keywords
    evolutionary computation; games of skill; neural nets; Hnefatafl; ancient Norse game; ancient game; board evaluation functions; board game; chess; evolutionary method; neural network; Artificial intelligence; Competitive intelligence; Computational intelligence; Evolutionary computation; Humans; Information science; Instruments; Neural networks; Evolution; Hnefatafl; board games;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Games, 2007. CIG 2007. IEEE Symposium on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    1-4244-0709-5
  • Type

    conf

  • DOI
    10.1109/CIG.2007.368094
  • Filename
    4219039