Has anyone tried doing pachi/Fuego + GnuGo hybrid slightly in way Many
FAces is done?
If I understood correctly Manyfaces is mostly a plausible move generator.
And serac is widened via the RAVE.
So simplest hybrid could rather simple words that often used before huge
effort taking for eve
> Yes. And while worrying about what happens after a win rate of 97%
> sounds like splitting hairs, I think we're talking about an awkward
> way of measuring something that's of practical interest.
Yes. How can a program be strong enough to win 97% and not win 100%.
Over on the fuego list Martin M
Yes. And while worrying about what happens after a win rate of 97% sounds like
splitting hairs, I think we're talking about an awkward way of measuring
something that's of practical interest.
Suppose Hideki's experiment were repeated, giving GNU GO a four stone handicap.
If Zen plateau'd out a
Alan Cameron wrote:
> introduce me to the science of artificial intelligence
such as would be employed in writing a computer go program?
I am not sure if it is what you are asking for but maybe it is: Search
for the following topics:
- computational complexity
- algorithm
Once you are famil
Hi!
On Sun, Jan 17, 2010 at 04:12:19PM -, Alan Cameron wrote:
> I have been reading this mailing list for some time as the subject interests
> me. I have a request - can anyone provide a reading list of books or web
> pages which would introduce me to the science of artificial intelligence
>
I think you can only evaluate static evaluation in the context of a search
and a tournament between programs. You could start with a simple 1-ply
search and play against gnugo. Strength in life and death or predicting pro
moves doesn't correlate with the ability to win games.
David
-Origina
Last year I was working on a static evaluation function.
Does anyone know references about published benchmark tests for static
evaluation functions, for example, in predicting moves in professional games
or best moves in life and death problems or predicting the status of
semeai problems?
The p
Hi,
I have been reading this mailing list for some time as the subject interests
me. I have a request - can anyone provide a reading list of books or web
pages which would introduce me to the science of artificial intelligence
such as would be employed in writing a computer go program?
Alan Camer
>
> This is very interesting, do you have pointers to any papers or
> presentations concerning MCTS applications like this in any detail?
> If not yet, I'm sure many people on this list will be interested
> to hear about any publications in this area too when you finish some
> of the applications
Hi!
On Sun, Jan 17, 2010 at 04:02:38PM +0100, Olivier Teytaud wrote:
> > I'm sure many people are curious - MoGo(TW?) doesn't participate much
> > in computer tournaments nowadays, are you working on some new exciting
> > things or is the project mostly asleep right now? :-)
>
> Competitions ar
> Apparently an opening book cannot be used with a stronger or weaker Go
> player as-is, but I wonder how useful it would be as a seed?
If we follows the "fictitious play" algorithm, maybe we should accept
a modification
of the opening book only after comparison with *all* previous versions
of the
> I'm sure many people are curious - MoGo(TW?) doesn't participate much
> in computer tournaments nowadays, are you working on some new exciting
> things or is the project mostly asleep right now? :-)
Competitions are very boring and time consuming. Other people from the mogo-team
can participate
Oh, ok. I was a bit surprised. Last time I checked my program scaled
quite nicely against GnuGo, at least for low numbers of simulations up
to about 97% winning rate. I suppose there could be some kind of
plateau when nearing 100% due to some missing knowledge/skills that
only GnuGo has.
Erik
20
13 matches
Mail list logo
