On 11.03.2016 08:24, Huazuo Gao wrote:
Points at the center of the board indeed depends on the full board, but
points near the edge does not.
I have been wondering why AlphaGo could improve a lot between the Fan
Hui and Lee Sedol matches incl. learning sente and showing greater signs
of more global, more long-term planning. A rumour so far suggests to
have used the time for more learning, but I'd be surprised if this
should have sufficed. So far, I have the following theories:
- deeper net
- greater parameters for convolutional patterns (instead of 5x5 and 3x3,
(also) use larger parameters) or combine the earlier parameters with
additional larger parameters or with an additional NN having only /
mostly larger parameters
- replace or enhance top KGS games by 100,000+ pro games
- instead of / in addition to feed forward nets, use long short term
memory nets (but I cannot know if this is advantageous considering
presumably greater GPU time)
- instead of single position patterns, use combinations of current
position and later positions, for different (dynamic) parameters of time
shift, so as to model long-term effects
--
robert jasiek
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