Hi,
Kensuke Matsuzaki released rn-6.3.0.
It is one of the strongest 9x9 engine.
It is "LeelaZero + 9x9 + heuristic features + adjustable komi + KataGo like
learning".
rn-6.3.0
https://github.com/zakki/leela-zero/releases/tag/rn-6.3.0
Rn.6.3
https://twitter.com/k_matsuzaki/status/1260908554359173120
Author says v995 is a latest model, but v945 is stronger.
And v995 tends to play (4,4) on initial position.
Thanks,
Hiroshi Yamashita
This is quote from README.md in zip file.
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# '9x9-endstate' branch
* For 9x9 game.
* Ladder detection (by https://github.com/yssaya/leela-zero-ladder)
* Various komi (by https://github.com/ihavnoid/leela-zero)
* Additional input features.
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# 'Endstate' branch
This is a fork of Leela Zero with the 'endstate' head. The 'stock' Leela Zero
uses the value and policy nets, while this also
predicts how the game ends. To do so, there are some changes:
* Additional 'endstate' head : The 'endstate' is how the game ended - that
information is also stored on the training data.
* Acceleration mode : To predict the endstate, we can't just resign when we
find the game hopeless - we have to play it to the end. Hence,
once we hit the resignation threshold, we reduce the playouts to 1 instead of
resigning.
* Using the 'endstate' information as the auxillary policy - see Network.cpp
for details on how it uses the auxilary policy
The main goal of this branch is to play reasonable handicap games (and to some
extent, play games with komi)
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