[Computer-go] Teaching Deep Convolutional Neural Networks to Play Go

Hiroshi Yamashita yss at bd.mbn.or.jp
Thu Dec 18 17:50:30 PST 2014


> One question: Is there a place where I can find sgf

Paper author, Christopher Clark kindly sent me sgf and let me share on ML.

This is a copy of sgf.

His notes is as follows.
Some notes:
The names of the 'players' are fuego, gnugo, gnugo_j (gnugo with Japanese rules), clf_gogod and clf_kgs for networks 
trained on the respective dataset, and clf_small for the smaller network trained on the gogod dataset.
In the archive, each prefix (0_xxx) corresponds to one round of games between two of these players. The metadata should 
contain all the details. Games against GNU Go and Fuego are in separate directories.
The networks were being run on a CPU and using some rather inefficient python code to convert the raw positions into the 
liberty encoding style needed as input, you can process positions much faster with a GPU and pre-encoded positions
I am hoping to open source this work soon, but it will take some time so that will not be ready until at least next 
A detail left out of the paper, for a few games against Fuego, Fuego was unable to score the final position. We have 
used GNU Go to rescore these games, I believe Fuego was the winner in all of these cases.

Best Regard,
Christopher Clark

Hiroshi Yamashita

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