It would reduce Alphago, because there is less training material in the form of high-dan-games, to train the policy network.
It would also reduce the skill of a human opponent, because (s)he would have less experience on a larger board, just as AlphaGo. It would be fun to see which can adapt better. Cheers Lukas On Wed, Mar 23, 2016 at 1:18 PM, Ray Tayek <rta...@ca.rr.com> wrote: > On 3/22/2016 11:25 AM, Tom M wrote: > >> I suspect that even with a similarly large training sample for >> initialization that AlphaGo would suffer a major reduction in apparent >> skill level. >> > i think a human would also. > >> The CNN would require many more layers of convolution; >> the valuation of positions would be much more uncertain; play in the >> corner, edges, and center would all be more complicated patterns, and >> there would be far more good candidates to consider at each ply and >> rollouts would be much less stable and less accurate. >> > yes. > > the normal board size is 19x19 because the amount of territory in the > sides and corners is slightly larger than the amount of territory in the > middle. > > thanks > > -- > Honesty is a very expensive gift. So, don't expect it from cheap people - > Warren Buffett > http://tayek.com/ > > > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go >
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