Congrats for breaking the 1000 elo mark on cgos. ;) Some things I
noticed when watching 2 games:
-stop plays on the first line/corner in the beginning. maybe this
helps: http://computer-go.org/pipermail/computer-go/2008-December/017340.html
or this:
Congrats for breaking the 1000 elo mark on cgos. ;)
Thanks!
Version 0.5 made quiet a difference compared to version 0.4.
I'm graphing the elo ratings of the versions running at cgos here:
http://keetweej.vanheusden.com/stats/stop-all-elo-cgos.png
Some things I noticed when watching 2 games:
Yes, known problem :-( I'm still trying to find a method to see if a
point is in an eye. Should not be too difficult in theory but in
practice i have not found a method yet.
Are you talking about 1 point eyes? For this I think most programs use
the same definition, which is quite good
In the last few weeks I have experimented a lot with dynamic
komi in games with high handicap. Especially, I used the
really nice commercial program Many Faces of Go (version 12.013)
with its Monte Carlo level (about 2 kyu on 19x19 board) and
its traditional 18-kyu level as the opponent.
At
2009/8/12 Ingo Althöfer 3-hirn-ver...@gmx.de
In the last few weeks I have experimented a lot with dynamic
komi in games with high handicap. Especially, I used the
really nice commercial program Many Faces of Go (version 12.013)
with its Monte Carlo level (about 2 kyu on 19x19 board) and
its
The small samples is probably the least of the problems with this. Do you
actually believe that you can play games against it and not be subjective
in
your observations or how you play against it?
These are computer-vs-computer games. Ingo is manually transferring moves
between two computer
Ingo suggested something interesting - instead of changing the komi according
to the move number, or some other fixed schedule, it varies according to the
estimated winrate.
It also, implicitly, depends on one's guess of the ability of the opponent.
An interesting test would be to take an
Ok, I misunderstood his testing procedure. What he is doing is far more
scientific than what I thought he was doing.
There has got to be something better than this. What we need is a way to
make the playouts more meaningful but not by artificially reducing our
actual objective which is to
Consider this thought experiment.
You sit down at a board and your opponent has a 9-stone handicap.
By any objective measure of the game, you should resign immediately.
All your win-rate calculations report this hopeless state of affairs.
Winrate gives you no objective basis to prefer one
I think Terry's suggestion is the best way to test these ideas:
1) Take 2 severely mismatched engines (perhaps 2 versions of the same engine
but with different numbers of playouts.)
2) Find the fair handicap by playing a sequence of games and adjusting the
number of handicap stones whenever
The problem with MCTS programs is that they like to consolidate. You set
the komi and thereby give them a goal and they very quickly make moves which
commit to that specific goal. Commiting to less than you need to actually
win will often involve sacrificing chances to win.Sometime it
Terry,
I understand the reasoning behind this, your thought experiment did not add
anything to my understanding. And I agree that if the program is strong
enough and the handicap is high enough this is probably better than doing
nothing at all.
However, I think there must be something that
I 100% agree with Don, dynamic komi just cant be the right approach in my
opinion.
One idea I just have is this :
In the tree search part, instead of using a rule wich converges to MAX, use a
rule wich converges to alpha*MAX + beta*AVERAGE. Do this only for plies where
it is the weaker player
Some algorithms are special-purpose by nature. What I sketched is an
approximation of my understanding of how strong players defeat weaker players
with large handicaps. When Myungwan Kim faced off against MFG a few days ago,
with a 7 stone handicap, he had to come up with a strategy which would
I started to write something on this subject a while ago but it got
caught up in other things I had to do.
When humans play a (high) handicap game, they don't estimate a high
winning percentage for the weaker player. They'll consider it to be
more or less 50-50. So to adjust the komi at the
Most experiments are done on even games; this dynamic algorithm applies
particularly to handicap games.In that context, it is not an ungainly kludge,
but actually reflects the assessment of evenly matched pro players - they look
at the board, and see a victory of n times 10 handicap stones ( or
On Wed, Aug 12, 2009 at 5:36 PM, Mark Boon tesujisoftw...@gmail.com wrote:
I started to write something on this subject a while ago but it got
caught up in other things I had to do.
When humans play a (high) handicap game, they don't estimate a high
winning percentage for the weaker player.
2009/8/12 terry mcintyre terrymcint...@yahoo.com
Most experiments are done on even games; this dynamic algorithm applies
particularly to handicap games.In that context, it is not an ungainly
kludge, but actually reflects the assessment of evenly matched pro players -
they look at the board,
2009/8/12 Don Dailey dailey@gmail.com:
I disagree about this being what humans do. They do not set a fake komi
and then try to win only by that much.
I didn't say that humans do that. I said they consider their chance
50-50. For an MC program to consider its chances to be 50-50 you'd
In practical terms, the problem to solve is the reverse: how do we encourage
weak programs to hang on to as much of their advantage as possible, against
stronger players?
In 2020, we can worry about how to beat pro players who take large handicaps
against computer programs.
Terry McIntyre
Don Dailey wrote:
The problem with MCTS programs is that they like to consolidate. You
set the komi and thereby give them a goal and they very quickly make
moves which commit to that specific goal.
How did you form this opinion? Can you show an example game record
(on 19x19) showing this
On Wed, Aug 12, 2009 at 5:58 PM, Mark Boon tesujisoftw...@gmail.com wrote:
2009/8/12 Don Dailey dailey@gmail.com:
I disagree about this being what humans do. They do not set a fake komi
and then try to win only by that much.
I didn't say that humans do that. I said they consider
What a bot does with its playouts in a handicap situation is to essentially try
to beat itself, despite the handicap.
And in this situation the bot reacts in a very human way, it becomes despondend.
Adjusting the komi dynamically shifts the goal from winning to catching up
quickly enough.
I
On Wed, Aug 12, 2009 at 6:03 PM, Matthew Woodcraft
matt...@woodcraft.me.ukwrote:
Don Dailey wrote:
The problem with MCTS programs is that they like to consolidate. You
set the komi and thereby give them a goal and they very quickly make
moves which commit to that specific goal.
How did
2009/8/12 Stefan Kaitschick stefan.kaitsch...@hamburg.de
What a bot does with its playouts in a handicap situation is to
essentially try to beat itself, despite the handicap.
And in this situation the bot reacts in a very human way, it becomes
despondend.
Adjusting the komi dynamically
What seems difficult to me however is to devise a reasonable way to
decrease this komi as the game progresses
Certainly that is the main problem. But the main considerations are not so
hard to find
1. Win rate of the best move.
2. How far has the game progressed
3. deviation between the win
As for how to beat weaker players ... the strong players whom I have observed
make strong, stable positions; they wait for the weaker player to make
mistakes. The stronger player will leave things unresolved for longer, knowing
that there will be time to extend in one direction or another later
For instance I am sure he will not sit merrily by and watch his opponent
consolidate a won game just so that he can have a respectable but losing
score.Dynamic komi of course does not address that at all.
This seems self evident, but it may actually be a treacherous conclusion.
Dynamic
Don Dailey wrote:
Matthew Woodcraft wrote:
Don Dailey wrote:
The problem with MCTS programs is that they like to consolidate. You
set the komi and thereby give them a goal and they very quickly make
moves which commit to that specific goal.
How did you form this opinion? Can you
2009/8/12 Don Dailey dailey@gmail.com:
If the program makes decisions about the best way to win N points, there
is no guarantee that this is ALSO the best way to win N+1 points.
Although this is obviously true, that doesn't automatically mean it's
not the best approach. Because there's a
No thought experiments are going to convince me on this subject.
Someone will have to do an actual test. Ingo's work is the best
to date on the subject.
Anyone who is overly committed to thought experiments should
consider that we are talking about applying MCTS to Go, that most
deterministic of
After about the 5th reading, I'm concluding that this is an excellent paper.
Is anyone (besides the authors) doing research based on this? There is a lot
to do.
David Silver wrote:
Hi everyone,
Please find attached my ICML paper with Gerry Tesauro on automatically
learning a simulation
On Aug 12, 2009, at 2:51 PM, Don Dailey wrote:
I disagree. I think strong players have a sense of what kind of
mistakes to expect, and try to provoke those mistakes. Dynamic
komi does not model that.
It also does the opposite of making the program play provocatively,
which I believe
On Aug 12, 2009, at 3:10 PM, Don Dailey wrote:
If the handicap is fair, their chance is about 50/50. However,
rigging komi to give the same chance is NOT what humans do. The
only thing you said that I consider correct is that humans estimate
their chances to be about 50/50.
One thing
Maybe they are long way from giving handicaps to you. But best of bots
in KGS are around 2k and there are hundreds of 9k and weaker players
present there at all times. So being able to play white is worthy
thing at least for commercial bot.
Petri
2009/8/13 Christoph Birk b...@ociw.edu:
On Aug
On Aug 12, 2009, at 3:43 PM, Don Dailey wrote:
I believe the only thing wrong with the current MCTS strategy is
that you cannot get a statistical meaningful number of samples when
almost all games are won or lost.You can get more meanful
NUMBER of samples by adjusting komi, but
On Aug 12, 2009, at 10:31 PM, Petri Pitkanen wrote:
Maybe they are long way from giving handicaps to you. But best of bots
in KGS are around 2k and there are hundreds of 9k and weaker players
present there at all times. So being able to play white is worthy
thing at least for commercial bot.
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