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Subject: Re: Chess, Backgammon and Neural Nets (NN)

Author: Bruce Cleaver

Date: 01:15:37 08/21/98

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On August 20, 1998 at 12:23:33, Torsten Schoop wrote:

>Hi all,
>
>does anyone know why NN backgammon programs play very well (TD-Gammon,
>JellyFish, Snowie)but the NN chess playing programs do not?
>
>Ciao
>Torsten


One reason that minimax is NOT successful in Backgammon is that the branching
factor is enormous (about 400 per ply, with dice throws) so a normal alpha-beta
search may only be able to get 2 or 3 ply on even a fast machine.   So, other
methods had to be found.

TD-Gammon went through several revisions, first with a raw board input, then
with hand coded primitives which substantially improved its play.  The
equivalent in chess would be normal eval stuff like passed pawns, hanging
pieces, king safety, good and bad squares, material advantage.  TD-Gammon also
played an enormous number of practice games to tune its NN (several hundred
thousand, or a few million, I cannot remember).  I bet if this sort of effort
were applied to chess, it could be successful.

Bruce






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