To take a normal evaluation function and convert it to a "probability of winning" function is probably difficult to do well. You might have to map some sort of curve where a few stones ahead represent a near win.
A simple approximation: - call the evaluation function - if it is less than zero, consider it one monte carlo run where white wins. If it's greater than zero, consider it a monte carlo run where black wins. It's probably better to use the curve - but my sense of it is that you need to map scores fairly accurately to odds of winning - to truly simulate a monte carlo run. How did you do this before? I think almost any reasonable idea is worth 2 or 3 tries - the devil is in the details. - Don On Sat, 2007-04-07 at 19:52 +0200, Chrilly wrote: > > > > I have this idea that perhaps a good evaluation function could > > replace the play-out portion of the UCT programs. The evaluation > > function would return a value between 0 and 1 and would be an > > estimate of the odds of winning. > > > I have tried this with an older and much weaker version of Suzie. It > played > positionally better than the Alpha-Beta version, but the rate of very > strange moves also increased. UCT greates a more unbalanced tree than > Alpha-Beta and the programm has therefore even more chances to > "cheat". For > the same reason extensions do not work so far in Suzie. > > But I tried not with 0-1 but used the full eval. Maybe I should give > it a > second try. But as I work now 45 hours/week on Computer-Tomography > (which is > also quite interesting) and comute each weekend between Germany and > Austria > its difficult to do. > > Chrilly > _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/
