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.
David > -----Original Message----- > From: Computer-go [mailto:computer-go-boun...@computer-go.org] On Behalf Of > Darren Cook > Sent: Tuesday, November 17, 2015 6:49 AM > To: computer-go@computer-go.org > 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 > > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go _______________________________________________ Computer-go mailing list Computer-go@computer-go.org http://computer-go.org/mailman/listinfo/computer-go
