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Blondie25,
an evolutionary chess program by David B. Fogel and Timothy J. Hays, supported by James Quon and Sarah L. Hahn. Blondie25 improved its play by almost 400 rating points during evolution [1].

New Results in Evolving Chess

Quote from the Press Release, May 22, 2006 [2]
Blondie25 is the result of over 8000 generations of variation and selection, simulated on a computer, in which a computer chess-playing program plays games against variations of itself to learn how to improve its play. Blondie25 includes mechanisms for learning the values of the pieces, their locations on the chessboard, and also uses neural networks to assess the formation of pieces in different areas of the board.

Publications


External Links


References

  1. ^ David B. Fogel, Timothy J. Hays, Sarah L. Hahn, James Quon (2004). A Self-Learning Evolutionary Chess Program. Proceedings of the IEEE, Vol. 92 No. 12, pp. 1947-1954, CiteSeerX
  2. ^ Natural Selection, Inc. Presents New Results in Evolving Chess Programs: Two Milestones in Self-Learning Chess Achieved | Natural Selection, Inc

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