Attempting to maximize the score is not compatible with being a strong engine.  
If you want a dan level engine it is maximizing win-probability.


> -----Original Message-----
> From: Computer-go [] On Behalf Of
> Darren Cook
> Sent: Tuesday, November 17, 2015 6:49 AM
> To:
> Subject: Re: [Computer-go] Strong engine that maximizes score
> > 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?)
> Darren
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