The non-mcts levels of Many Faces try to maximize score, with some bias toward 
safety when ahead.  The non-MCTS version uses dynamic komi to avoid giving up 
points in the endgame, but this is not in the version 12 released engine.




From: Computer-go [] On Behalf Of 
Chun Sun
Sent: Tuesday, November 17, 2015 7:15 AM
Subject: Re: [Computer-go] Strong engine that maximizes score


taking my question back. the answer is no in the context of mcts.


On Tue, Nov 17, 2015 at 10:10 AM, Chun Sun <> wrote:

Is the last requirement equivalent to dynamic komi?


On Tue, Nov 17, 2015 at 9:49 AM, Darren Cook <> wrote:

> I am trying to create a database of games to do some machine-learning
> experiments. My requirements are:
>  * that all games be played by the same strong engine on both sides,
>  * that all games be played to the bitter end (so everything on the board
> is alive at the end), and
>  * that both sides play trying to maximize score, not winning probability.

GnuGo might fit the bill, for some definition of strong. Or Many Faces,
on the level that does not use MCTS.

Sticking with MCTS, you'd have to use komi adjustments: first find two
extreme values that give each side a win, then use a binary-search-like
algorithm to narrow it down until you find the correct value for komi
for that position. This will take approx 10 times longer than normal
MCTS, for the same strength level.

(I'm not sure if this is what Pachi is doing?)


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