• DocumentCode
    3498036
  • Title

    The Blondie25 Chess Program Competes Against Fritz 8.0 and a Human Chess Master

  • Author

    Fogel, David B. ; Hays, Timothy J. ; Hahn, Sarah L. ; Quon, James

  • Author_Institution
    Natural Selection Inc., La Jolla, CA
  • fYear
    2006
  • fDate
    38838
  • Firstpage
    230
  • Lastpage
    235
  • Abstract
    Previous research on the use of coevolution to improve a baseline chess program demonstrated a performance rating of 2650 against Pocket Fritz 2.0 based on 16 games played (13 wins, 0 losses, 3 draws). The resultant program, named Blondie25, did not use any rules for managing the time allocated per move; it simply used three minutes on each move. Heuristics to more effectively manage time were developed by trial and error, play testing against Fritz 8.0. The best heuristics discovered were different for black and white. The results of 12 games played on each side were 1 win, 4 losses, and 7 draws for black, and 2 wins, 6 losses, and 4 draws for white. Fritz 8.0 is rated currently at 2752 (plusmn20) on SSDF (the acronym for the Swedish Chess Computer Association), placing it as the 12th strongest program in the world. At the time of the contest between Blondie25 and Fritz 8.0, Fritz 8.0 was rated #5 in the world. The results are the first case of an evolved chess program defeating a world-class chess program (three times). The performance rating for Blondie25 against Fritz 8.0 was 2635.33, which compares well with the previous performance rating of 2650 against Pocket Fritz 2.0. Blondie25 was then tested against a nationally ranked human chess master, rated 2301. In four games, Biondie25 won three and lost one
  • Keywords
    computer games; Blondie25 chess program; Fritz 8.0; Pocket Fritz 2.0; human chess master; Artificial intelligence; Automatic testing; History; Humans; Learning; Minimax techniques; Neural networks; Performance loss; Protocols; Vehicle crash testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Games, 2006 IEEE Symposium on
  • Conference_Location
    Reno, NV
  • Print_ISBN
    1-4244-0464-9
  • Type

    conf

  • DOI
    10.1109/CIG.2006.311706
  • Filename
    4100133