Sylvain, The improvement over a given opponent should be measured by ELO points, not win percentage unless you do the extra math. I cannot quite tell if you were considering that or not - if so then ignore this. Going from 50% wins to 60% with is a modest improvement, but going from 80% to 90% is a MAJOR improvement.
UCI is completely scalable, but may not be optimally scalable. It may turn out that there are other ways to handle the best first search. My fear with UCI type methods is that it might be progressively less efficient as you get much faster. It is probably a matter of finding just the right formula for allocating work. Or it might turn out that some form of alpha/beta search using monte/carlo as an evaluator is the right thing given enough power - which suggests some kind of hybrid approach. UCI may be the best way to handle nodes closer to the leaf and perhaps be viewed as a kind of quies search for a standard alpha/beta engine. I'm just taking a wild guess here. - Don On Thu, 2006-11-23 at 13:24 +0100, [EMAIL PROTECTED] wrote: > > I think they will play very strong. Sofar all my tests indicates nice > > scaling, but I admit I have not tried a proper experiment for a long time > > since I do not have any extra hardware. Perhaps the Mogo team could do > >something but the problem is that Mogo is so strong it would beat most > >programs 100% with modest increases in computation time on 9x9. > > What we can say from experiments is that the scaling with time is very good > with few simulations, but becomes less interesting with a lot of simulations. > With the same settings (not the best, but the ones for which we have the most > number of results), against gnugo at level 0 (s/m == simulations/move): > 3000 s/m : 35%, 10000 s/m : 60%, 70000 s/m : 90%. Against gnugo at level 8 > (default) it gives respectively 50% and 80% for 10k s/m and 70k s/m. > MoGo on cgos plays with something like 300k s/m, but I don't think it is much > better than with 70 k s/m. Quick experiments showed that the improvement was > only few % against gnugo. However, I saw that the improvement is larger > against MC based programs (classical non transitivity of the results), and > against itself it is huge. > I also saw that after each improvement, the number of simulations was less > important than before, so the scaling is less impressive. > Perhaps it comes from the fact that now the opening moves are those where > MoGo > loses most of its games and, as Magnus said, the number of simulations are > not so important in the opening. We did not investigate that. > > Sylvain > > _______________________________________________ > computer-go mailing list > computer-go@computer-go.org > http://www.computer-go.org/mailman/listinfo/computer-go/ _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/
