[Computer-go] CGOS source on github
lightvector at gmail.com
Fri Jan 22 06:13:02 PST 2021
On Fri, Jan 22, 2021 at 3:45 AM Hiroshi Yamashita <yss at bd.mbn.or.jp> wrote:
> This kind of joseki is not good for Zero type. Ladder and capturing
> race are intricately combined. In AlphaGo(both version of AlphaGoZero
> and Master) published self-matches, this joseki is rare.
> I found this joseki in kata1_b40s575v100 (black) vs LZ_286_e6e2_p400
Hi Hiroshi - yep. This is indeed a joseki that was partly popularized by AI
and jointly explored with humans. It is probably fair to say that it is by
far the most complicated common joseki known right now, and more
complicated than either of the avalanche or the taisha.
Some zero-trained bots will find and enter into this joseki, some won't.
The ones that don't play this joseki in self-play will have a significant
chance to be vulnerable to it if an opponent plays it against them, because
there are a large number of traps and blind spots that cannot be solved if
the net doesn't have experience with the position. And even having some
experience is not always enough. For example, ELF and Leela Zero have
learned some lines, but are far from perfect. There is a good chance that
AlphaGoZero or Master would have been vulnerable to it as well. KataGo at
the time of 1.3.5 was also vulnerable to it too - it only rarely came up in
self-play, and therefore was never learned and correctly evaluated, so from
the 3-3 invader's side the joseki could be forced and KataGo would likely
mess up the joseki and be losing the game right at the start. (The most
recent KataGo nets are much less vulnerable now though).
The example you found is one where this has happened to Leela Zero. In the
game you linked, move 34 is a big mistake. Leela Zero underweights the
possibility of move 35, and then is blind to the seeming-bad-shape move of
37, and as a result, is in a bad position now. The current Leela Zero nets
consistently makes this mistake, *and* consistently prefer playing down
this line, so against an opponent happy to play it with them, Leela Zero
will lose many games right in the opening all the same way.
Anyways, the reason this joseki is responsible for more such distortions
than other joseki seems to be because it is so sharp, and unlike most other
common joseki, contains at least 5-6 enormous blind spots in different
variations that zero-trained nets variously have trouble to learn on their
> a very large sampling of positions from a wide range
> > of human professional games, from say, move 20, and have bots play
> > from these sampled positions, in pairs once with each color.
> This sounds interesting.
> I will think about another CGOS that handle this.
I'm glad you're interested. I don't know if move 20 is a good number (I
just threw it out there), maybe it should be varied, it might take
some experimentation. And I'm not sure it's worth doing, since it's still
probably only the smaller part of the problem in general - as Remi pointed
out, likely ladder handling will be a thing that always continues to
introduce Elo-nontransitivity, and probably all of this is less important
than generally having a variety of long-running bots to help stabilize the
system over time.
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the Computer-go