On 3/22/2016 5:21 PM, Lukas van de Wiel wrote:
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.
human would adapt quickly after a few games (say 10 or so).
thanks
On Wed, Mar 23, 2016 at 1:18 PM, Ray Tayek <rta...@ca.rr.com
<mailto: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/
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Honesty is a very expensive gift. So, don't expect it from cheap people -
Warren Buffett
http://tayek.com/
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