Author: Jay Scott
Date: 12:35:44 01/04/99
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On January 04, 1999 at 15:10:07, James Robertson wrote: >On January 04, 1999 at 14:21:31, Jay Scott wrote: > >>One idea about why it works so well in backgammon is that the >>in backgammon the dice force a self-play program to explore all the >>important parts of the game space. In chess, a learning program can make >>the same mistakes over and over and never correct them because it doesn't >>know how to punish them. > >Well; they know how to punish them, but they don't know why. All they know is >that they won the game at the end. The problem with chess learning is that every >aspect learned must be put in by the program by the programmer. e.g. if the >programmer puts piece/square table learning in, the program learns piece/square >tables. If they put doubled pawn awareness in, the program fiddles with the >doubled pawn scoring. And so on... It depends, of course. If the programmer puts in the basic position info (this set of squares has white pawns...) and allows the program to combine it arbitrarily, then in principle the program can learn anything. For example, self-play learning would make sense for a genetic programming system, which could do this. It happens that nobody has gotten a genetic programming system to successfully learn anything this difficult yet, but there's no obstacle in principle. It's those darn practical details! :-) Jay
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