Is the last requirement equivalent to dynamic komi? On Tue, Nov 17, 2015 at 9:49 AM, Darren Cook <dar...@dcook.org> 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?) > > 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
