I seriously doubt a highly optimized MoGo would be able to stay this close to uniform random in speed.
It's already been pointed out that a lot of MoGo is infrastructure to support interesting experiments. I'm guessing here, but my guess is that the uniform random implementation is suffering more from the baggage of this infrastructure than the best simulation policy version that I would guess is benefitting more from this infrastructure. Am I right or wrong Sylvain? - Don On Sat, 2007-02-03 at 10:31 -0800, David Doshay wrote: > On 3, Feb 2007, at 2:51 AM, Sylvain Gelly wrote: > > > the speed of the best simulation policy in MoGo is 0.6 * the speed > > of the uniform random one. > > I think that this is very good. You give up less than a factor of 2 > from uniform random and you probably get better than a factor of 2 in > the % of relevant moves. > > This has been the biggest reason we have delayed adding MC to SlugGo: > how do you keep the "randomly" selected moves anywhere near the > relevant moves? With the high branching factor we face in Go, this > seems most important to me. And MoGo has made huge strides in that > direction. > > > > Cheers, > David > > > > > > _______________________________________________ > 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/
