Hi,
Our program Natsukaze also used Leela Zero recent 700000 selfplay games
to train DNN.
Ladder escape moves(4% of total games) are removed, and chasing not
ladder(0.3%) also removed. But its DNN policy was weak, around CGOS 2100.
Maybe it is because current LZ selfplay use t=1 not first 30 moves but all
moves.
I did not know this. I think this makes selfplay weaker +1000 Elo.
Switch to t=1 for all self-play moves, i.e., randomcnt=999
https://github.com/gcp/leela-zero-server/pull/81
Thanks,
Hiroshi Yamashita
On 2018/12/19 2:01, Gian-Carlo Pascutto wrote:
On 17/12/18 01:53, Hiroshi Yamashita wrote:
Hi,
AI Ryusei 2018 was held on 15,16th December in Nihon-kiin, Japan.
14 programs played preliminary swiss 7 round, and top 6 programs
played round-robin final. Then, Golaxy won.
Result
https://www.igoshogi.net/ai_ryusei/01/en/result.html
It appears the 2nd place finisher after Golaxy was a hybrid of Rn and
Leela Zero, using rollouts to compensate for Leela's network being
trained with the "wrong" komi for this competition:
https://github.com/zakki/Ray/issues/171#issuecomment-447637052
https://img.igoshogi.net/ai_ryusei/01/data/11.pdf
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