Fwd: [Computer-go] Representing Komi for neural network

[Steve Kroon]

Hey Francois.

As per the query below, it would be cool if we could include a link to
Detlef's fork on either the Oakfoam.com website (or at least the front
page of the bitbucket repo wiki) - at least until we one day manage to
do a merge :)

Steve

---------- Forwarded message ----------
From: Aja Huang <ajah...@gmail.com>
Date: Sun, Jan 11, 2015 at 11:41 PM
Subject: Re: [Computer-go] Representing Komi for neural network
To: compu...@computer-go.org




2015-01-11 15:59 GMT+00:00 Detlef Schmicker <d...@physik.de>:
>
> By the way:
> Todays bot tournament nicego19n (oakfoam) played with a CNN for move prediction.
> It was mixed into the original gamma with some quickly optimized parameter leading to >100ELO improvement for selfplay with 2000 playouts/move. I used the Clark and Storkey Network, but with no additional features (only a black and a white layer). I trained it on 60000 kgs games and reached about 41% prediction rate. I have no delayed evaluation, as I evaluate no mini-batch but only one position taking about 1.6ms on the GTX-970. A little delay might happen anyway, as only one evaluation is done at once and other threads might go on playing while one thread is doing CNN. We have quite slow playouts anyway, so I had around 70000 playouts/move during the game.
>
> If you want to get an impression, how such a bot plays, have a look at the games :)


Congrats on oakfoam's significant improvement with the CNN. The game
oakfoam beat HiroBot[1d] is very nice

http://files.gokgs.com/games/2015/1/11/HiraBot-NiceGo19N.sgf

Would you release the newest version of oakfoam and the CNN? I
couldn't find your git or svn repository at

http://oakfoam.com/#downloads

Aja


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