Thomas Nelson wrote: > Hi, my name's Tom, and I'm a computer science undergraduate at UT > Austin. I'm doing a research project on machine learning in go. My > plan is to choose ~10 patterns in the gnugo patterns database, and > optimize the shape() values for the patterns using a kind of gradient > descent learning. My question is, which patterns should I choose? > Ideally, I want to choose the 10 that will have the biggest effect on > gnugo's performance. They should be used pretty often, and preferably > early in the game. My current plan was just to play a lot of games, > and use > gnugo -l [filename] -L [move number] -t -a -w > on each move to see which patterns get selected most often. But maybe > someone knows a particular group or type of pattern that needs more > attention, or a more efficient way to search for important patterns?
I'm doubtful there are any patterns which are really suitable for your plan. I think it would be more interesting to do the experiment with some selection of coefficients more centrally involved in the move valuation, e.g. the ones in connection_value() in value_moves.c, in crude_dragon_weakness() in dragon.c, and/or in compute_dragon_weakness_value() in dragon.c. /Gunnar _______________________________________________ gnugo-devel mailing list [email protected] http://lists.gnu.org/mailman/listinfo/gnugo-devel
