Author: Sune Fischer
Date: 05:03:40 12/29/01
Go up one level in this thread
On December 29, 2001 at 07:48:38, Tom Kerrigan wrote: >>Still you dimensional search space is very large, and with each concensus eval >>that expensive, you can't really afford a sloppy approach. >>Genetic algorithms might do the job if you can define a good consensus/scoring >>function, which is no trivial thing to do in the first place. >> >>-S. > >I think we're talking about different algorithms. My idea is for making a >program play a known-good move, not to find ideal values for all eval weights. Well possibly, but when I read point number 3 I still see you comparing scoring values (getting the deltas) and then apply a "sloppy" (no offense:) arbitrary change in the weights. This can be done better I think, there is a lot of stuff on tuning weights in the litterature, genetic algorithms is one of the really big guns, and I believe this situation calls for some heavy artillery. >The hope is that if you force the program to make enough good moves, the eval >weights will end up being pretty good. I'll buy that, this is one way of defining a consensus function. -S. >-Tom
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