comments about the new playing style from strong as well from weak
players.
Best
Magnus
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gomorra passes 3 times before it resigns.
Of course, its not optimal :)
I wonder if there are others who haven't implemented the pass move
but found a nice way of handling seki situations during the search?
- Lars
-Ursprüngliche Nachricht-
Von: Magnus Persson magnus.pers...@phmp.se
of some size. A joseki dictionary can
be seen as using very large patterns.
-Magnus
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I was not at all surprised by this result.
My thinking goes like this. On 9x9 the global situation is everything
that matters and precomputed information is not as important as
searching effectly is. Good 9x9 games are often very sharp fights
where then next move often violates good shapes
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Quoting Petr Baudis pa...@ucw.cz:
On Thu, Sep 10, 2009 at 01:54:49PM +0200, Magnus Persson wrote:
This is very interesting. Here is a crazy idea, maybe it the same as
Marks but I want to take it to its extreme.
Since AMAF values are so helpful, perhaps one can let go of the idea
of sequential
. And then
copy many copies of that position and evaluate them massively in
parallel.
-Magnus
Quoting Petr Baudis pa...@ucw.cz:
On Thu, Sep 10, 2009 at 01:54:49PM +0200, Magnus Persson wrote:
This is very interesting. Here is a crazy idea, maybe it the same as
Marks but I want to take it to its extreme
of rules will probably make
it more biased than a usual light playout. Hard to tell before trying.
My feeling is that it might work surprisingly well but it might get
extremely biased in some situations, which perhaps can be fixed by
prefiltering of the move that can be played.
Magnus
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Peter Drake
http://www.lclark.edu/~drake/
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term
goal.
Stefan
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X X
F - X O - X O O O X
G - X O - X O O - O
H O X O - X X O O -
J - - - O X - X O -
O to play
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I also tried dynamic komi with Valkyria a long time ago. It failed. I
did not waste much time on it. Anyway here are my opinions and
intuitions about it.
As usual I am open to been proved being wrong with some empirical
evidence along with a nice algorithm that I can steal and add to
?
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strength.
-Magnus
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Quoting Darren Cook dar...@dcook.org:
* The scaling behavior might be different. E.g. if Fuego and Valkyria
are both run with 10 times more playouts the win rate might change. Just
to dismiss an algorithm that loses at time limits that happen to suit
rapid testing on today's hardware could mean
strength from it would seem like comparing apples and
oranges.
Christian
Magnus Persson wrote:
Quoting Darren Cook dar...@dcook.org:
* The scaling behavior might be different. E.g. if Fuego and Valkyria
are both run with 10 times more playouts the win rate might change. Just
to dismiss an algorithm
. o o * . .
|o * o . * . .
|o o o * . . .
|. * * * . . .
|. . . . . . .
|. * . . . . .
Black to play and kill :)
Christian
On 01/07/2009 17:41, Magnus Persson wrote:
In this case one needs to check that after the two stones are
captured the capturing single stone can be recaptured bringing us
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for lifedeath?
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Quoting Nick Wedd n...@maproom.co.uk:
In message 20090622202905.utvbb8wkgk8cw...@webmail.phmp.se, Magnus
Persson magnus.pers...@phmp.se writes
I looked at the report and would like to give my opinion on why the
programs played as they did in the commented game between Zen and
Aya
Quoting Brian Sheppard sheppar...@aol.com:
What komi did you use? It is nice to have the sgf in addition to the
position.
It is 7.5, and I do not have the SGF. I will try to create SGF for future
posts, to make reproduction easier for all.
Could it be that Pebbles have trouble seeing that
.
Does this literally mean using the win ratio (with one dummy win per
node) to decide paths through the MC tree? It seems that the best move
could easily be eliminated by a couple of bad runs.
Does this only work when using RAVE/AMAF?
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.
-Magnus
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Probably 1x1 patterns implies that different priorities are assigned
to the absolute position of empty moves. AMAF can be seen this way.
AMAF learns statistics of 1x1 patterns if the move is played in the
playout but ignores all information surrounding the move at the time
it is played.
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I think all principles I use in the time management for Valkyria came
up in this thread more or less.
1) Valkyria selects move that has been searched the most.
2) It is given a base time for example 20 seconds early on on 9x9 CGOS
3) The base time is adjusted down if the program is winning
information from
trials.
Best,
Brian
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Actually, MCTS-programmers should be happy with any timeconstraints
that does not make the program run out of memory, since a proper
MCTS-program should scale nicely no matter the time constraint. Maybe
an ultrafast tournament with a tenth of a second would favor Valkyria
on small boards
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Hi, as usual Valkyria seems to handle this position well at the price
of being a super slow program in general.
This is just one example of how it reacts.
After 100 simulations it treats F1 as the best almost always, having
searched 30 to 100 times. Perahps 50-70 times is the most common
Quoting Brian Sheppard sheppar...@aol.com:
OK, so you don't have to worry if you set c==0. It might even be best. Just
a note: in very preliminary
experiments, c==0 is not best for Pebbles. If longer experiments confirm
that, I presume it is because
Pebbles runs on a very slow computer and
/
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on the 9x9 server just so that people would have
something to play against and Brain might be able to get things tested.
I'm also updating the archives, since December though Feb is missing.
- Don
-Original Message-
From: Magnus Persson magnus.pers...@phmp.se
Reply-To: computer-go computer-go
Quoting Sylvain Gelly sylvain.ge...@m4x.org:
On Wed, Jan 28, 2009 at 10:01 PM, Isaac Deutsch i...@gmx.ch wrote:
And a final question: You calculate the (beta) coefficient as
c = rc / (rc+c+rc*c*BIAS);
which looks similar to the formula proposed by David Silver (If I recall
his name
Quoting Sylvain Gelly sylvain.ge...@m4x.org:
On Fri, Jan 30, 2009 at 9:29 AM, Magnus Persson
magnus.pers...@phmp.sewrote:
Did you try to tune the bias constant at all or just took the one I posted?
I wrote it from memory and I believe it is in the range of possibly good
values
, and would also fail miserably in such positions.
Best
Magnus
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Quoting Thomas Lavergne thomas.laver...@reveurs.org:
- the best play is a good only if played immediatly and very bad if
played later in the game :
- the first playout for this play resulted in a lost.
score and RAVE score will be very low and this play will never be
considered again
the coefficent goes 1
which is how this function should behave.
Magnus
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I could find anything problematic with your specification so I just
make some comments.
Quoting Mark Boon [EMAIL PROTECTED]:
- When it reaches N simulations, the child of the root-node with the
best wins-visits ratio is played. I've also seen that simply the child
with the highest number of
Quoting Mark Boon [EMAIL PROTECTED]:
Thanks for the comments Magnus.
On 20-nov-08, at 13:00, Magnus Persson wrote:
The way I understood the article, after a playout it updates all the
nodes at the current level of all the moves played during the playout
(if it's a win for the player
pass because I changed it so many times
and had to add a lot of kludges to avoid problems with older kludges
and so on...
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I use a method inititally from the Mogo team that sorts of randomizes
the position before running the heavy playout. One simply plays
uniformly random *non contact* moves. The effect of this is that it
preserves the shapes of stones on the board, but it prevents the heavy
playouts from
a hard case for that.
Mark
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Quoting Hideki Kato [EMAIL PROTECTED]:
Heikki Levanto: [EMAIL PROTECTED]:
The way I understand it, modern Monte Carlo programs do not even try to
emulate a human player with a random player - obviously that would not work.
I believe CrazyStone's use of patterns does so and it seems
Yes, Valkyria does a lot of ladder reading as well. Actually pattern
matching in the case of Valkyria is a little unclear, it is a
decision trees where the leaves are often procedure calls that looks
at a larger portion of the board. The ladder code is called for
various reasons in the
stronger on equivalent hardware using normal time controls.
If I turned off AMAF for Valkyria I would probably have to retune all
parameters to make a fair comparison, but I am quite sure that crudely
turning it off would be very bad.
Magnus
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Valkyria does, because is superheavy anyway! A lot of weird stuff can
happen near the end of the game against programs that play randomly. I
think I implemented it because I had to to make it play correctly in
some positions. But it was a long time so I do not remember the details.
-Magnus
No, if there was a serious problem it would perhaps only happen for 1
in 1000 games. So it would be pointless trying to measure it. And some
of these problems only happens against extremely weak programs. At
least in my experience.
-Magnus
Quoting Michael Williams [EMAIL PROTECTED]:
I
I checked these variation myself and with valkyria and it seems to be
sensible.
-Magnus
Quoting Don Dailey [EMAIL PROTECTED]:
I took all the games played by Leela in my 6x6 experiment and applied
mini-max to them, taking the statistics at various depths into the
games.
Don't know if there
I fear we are not talking about the same game. In case I made a
mistake in my email you get the sgf here:
(;FF[4]CA[UTF-8]AP[GoGui:1.1]SZ[6]
KM[2.5]DT[2008-09-30]RE[B+Resign]
;B[cc];W[dd];B[cd];W[dc];B[db];W[eb];B[de];W[ee];B[ed];W[ec]
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Quoting [EMAIL PROTECTED]:
See comments below...
... bE3 wE4 bE1 wF3!!!...
Normally wF2 is played in the corner. But with wF3 white has the
option to play aggresively with wF1 which usually is a bad idea
because the ko fight risk to much. But on a small board things are not
normal...
Can I
I have been trying to see what Valkyria does. But it is a little
unstable when it reads deep at 6x6. It should not be a problem for
Valkyria but I have not had any time to search for the bug.
Anyway the 2.5 komi black should lose if Don is right. So I have the
following very cute complete
Quoting Ingo Althöfer [EMAIL PROTECTED]:
Hello Magnus,
interesting and strange.
I went through your constructed game (it is repeated here
without the in-between text)
bC4 wD3 bC3 wD4 bD5 wE5 bD2 wE2 ...
... bE3 wE4 bE1 wF3!!!...
... bC1 wC5 bB5 wD6 bB6 wF1!...
...bF2 wC6 bB4!
...wF1 bE6
I stubbornly always use x.5 komi because I do not like Jigo. in this
case it was 2.5. I do that simply because Valkyria is coded like that,
it cannot play with integer komi.
Quoting Christoph Birk [EMAIL PROTECTED]:
On Tue, 30 Sep 2008, Magnus Persson wrote:
...wF1 bE6 wF6 bF2 wE3 bD1 wF1
Quoting Mark Boon [EMAIL PROTECTED]:
Playing out that fake ladder in the first game meant an instant loss.
Surprising. And embarassing. Any information on the number of
processors used?
The interesting question is if there is a silly bug or something more
sophisticated.
I have struggled
not elegant, rarely matter.
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Quoting David Fotland [EMAIL PROTECTED]:
Can you put crazystone back on 19x19 so I can see if it is just a fluke
against fuego?
I added locality to the light playouts - play near last or second to last
move, and some code to handle long ladders in playouts. I dont think this
is anything
I will also run Valkyria on CGOS 13x13 over the weekend, (or long as
things are stable).
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The program reivax on 9x9 CGOS seems to be strong but suffer from a
bug leading it to pass too early, and thus it often loses games
against weaker programs that do not resign.
-Magnus
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Some months ago someone published a set of LD problems made for MCTS
programs. Going through this I found a lot of serious bugs in Valkyria
where overly aggressive pruning removed tesujis (tesuji = move that
normally should be pruned).
After that Valkyria improved perhaps 50-100 Elo. But I
Quoting Jacques Basaldúa [EMAIL PROTECTED]:
When you detect self atari in the playouts (something I haven't
tried yet, but
from recent posts in this group I am convinced that it is an important issue)
a new problem arises: How can you score the board _fast_ at the end?
Valkyria makes a
I looked at the last games played by rz-74, and it looks like a
MC-program given how how it plays in the opening (odd moves in the
center). I also doubt there are any traditional programs who can get
90% against gnugo on 19x19. Are there?
But it seems to overplay badly in the opening in
on the strength of the program.
With 9x9 I have used many systems learned or handmade, but it all
boils down to that as been said earlier. It only works for a program
that does not change, since it overfits its own strengths and
weaknesses.
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Quoting Don Dailey [EMAIL PROTECTED]:
Yes, UCT is easier to use with multiple CPU's because with additional
processors alpha-beta programs do wasted work, unless you are talking
about theoretical programs with perfect move ordering, which you aren't.
Nice that all is clear about alpha-beta
Quoting Hideki Kato [EMAIL PROTECTED]:
Yes, UCT does. From my recent experiments with a delay
line (a fixed size FIFO queue) between a UCTsearcher and an MC
simulator with RAVE against GNU Go 3.7.11 level 0 on 9x9 (single
thread):
delay #po winsgames winning rateELO 1
I think most programs developed by people who did not write old scool
programs has serious problems with seki. Valkyria detects some basic
seki shapes, but has problems with nakade/seki.
-Magnus
Quoting Erik van der Werf [EMAIL PROTECTED]:
You're right, my reply was sloppy (it seems I'm
6813
%section player
name Gnugo-3.7.10-a1
password somePassword
invokegnugo --mode gtp --score aftermath --capture-all-dead
--chinese-rules --min-level 10 --max-level 10 --positional-superko
priority 7
On Sun, 2008-08-03 at 00:26 +0200, Magnus Persson wrote
cgos.boardspace.net -port 6813
- Don
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be interesting to see the difference.
Best
Magnus
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Actually it is only the updating of the webpage that does not work.
The programs play as usual.
Quoting Urban Hafner [EMAIL PROTECTED]:
Seems like it's down since the 29th.
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Quoting Carter Cheng [EMAIL PROTECTED]:
1) How typically do UCT bots score simulations quickly? I am not too
familiar with Chinese scoring rules.
In the end of a random games. There are only Black stones and Black
Eyes, as well as White stones and eyes. If your playouts are smart
enough
I have already posted the following results. The results shows the
winrates of Valkyria 3.2.0 against gnugo at default strength.
512 Simulations per move
UCT_K Winrate SERR
0 58.82.1 (Winrate only)
0.0156.82.2
0.1 60.92.2
0.5 54.22.2
1 50.62.2
Quoting David Fotland [EMAIL PROTECTED]:
So I'm curious then. With simple UCT (no rave, no priors, no progressive
widening), many people said the best constant was about 0.45. What are the
new concepts that let you avoid the constant?
Is it RAVE, because the information gathered during the
Quoting Michael Williams [EMAIL PROTECTED]:
I'm curious what the winrate of the bug-fixed version is over the
original version.
The last version with bugs was Valkyria3.2.0 with 2216 Elo on CGOS,
whereas the new version Valkyria3.2.1 currently has 2255. It is doing
really well against
I have checked if there is a difference for Valkyria in using
confidence bounds or just greedily search the move with the highest
winrate. This is Valkyria 3.2.0 using 512 simulations per move against
GnuGo 3.7.10.
UCT_K Winrate SERR
0 58.82.2 (greedy)
0.0156.82.2
0.1
I run it with
gnugo3.7.10.exe --mode gtp --chinese-rules --score aftermath
--capture-all-dead --positional-superko
Which is the default level which I do not know what it is.
-Magnus
Quoting David Fotland [EMAIL PROTECTED]:
What level for gnugo 3.7.10?
I went through the problems with Valkyria.
Right now it can do 32 out 50 where it had to think more than 10
seconds on perhaps 2 of those problems it solved.
But I do recommend to go through these problems by hand. At least one
position had the first move right but it seemed very week on
Quoting Olivier Teytaud [EMAIL PROTECTED]:
Also, I've met people claiming that
- they need a constant 0 for exploration;
I use 0.1*Sqrt( ln(totvisits)/(5*Visits));
The 5 in the equations is there for historical reasons.
But I think the advantage I get from a constant 0 is so small it is
do right now is that I only use the first 70% of the
moves played in the simulations for AMAF, following the idea that
moves at the end of each simulations probably is only noise anyway.
-Magnus
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Yesterday I noticed an odd phenomena in Valkyria wich was caused by
high selectivity and AMAF.
In this position
(;GM[1]FF[4]SZ[9]AP[SmartGo:1.4]
KM[7.5]
;B[ee];W[de];B[ed];W[df];B[ef];W[dd];B[dg];W[ge];B[dc];W[cc];B[cd];W[bd]
No, I can read it without problems on windows.
Quoting Jacques Basaldúa [EMAIL PROTECTED]:
and I still cannot read any mathematical expressions. I guess this
applies to all Windows users.
-Magnus
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A recurrent concept popping up in discussions on how to improve
playouts is balance. So I would like to try to share my philosophy
behind the playouts of Valkyria and how I define balance and how it
relates to the evaluation of go positions.
*Background
In an old school program the
Quoting Don Dailey [EMAIL PROTECTED]:
I have a response to this comment:
Still I think predicting the best moves is very important in the
tree part, but this may be much less important in the playouts, and
perhaps even detrimental as some people have experienced.
A class of bad
Quoting Petr Baudis [EMAIL PROTECTED]:
Please note that pachi1 had a rather embarassing bug of starting the
random playouts with wrong color (so if the last tree node was black,
the playout would start with black as well). pachi2 has this bug fixed;
the ELO rating is still not settled, but so
Quoting Ivan Dubois [EMAIL PROTECTED]:
Hello,
I think there is a very easy and straigthforward solution to the
nakade/seki problem, here it is :
For moves that are self-atari on a group that contains MORE than
5 stones :
Both in the tree and the playouts, strictly forbid them
Quoting Don Dailey [EMAIL PROTECTED]:
When the child nodes are allocated, they are done all at once with
this code - where cc is the number of fully legal child nodes:
In valkyria3 I have supernodes that contains an array of moveinfo
for all possible moves. In the moveinfo I also store
Quoting Jonas Kahn [EMAIL PROTECTED]:
On Tue, Mar 11, 2008 at 09:05:01AM +0100, Magnus Persson wrote:
Quoting Don Dailey [EMAIL PROTECTED]:
When the child nodes are allocated, they are done all at once with
this code - where cc is the number of fully legal child nodes:
In valkyria3 I have
Attached is an sgf-game of a long kofight on 9x9 between Valkyria and
Gnugo. Valkyria of course wins with 0.5 otherwise it would probably
not have been such a nice example of a long kofight.
-Magnus
kofight318392.sgf
Description: application/go-sgf
Quoting Mark Boon [EMAIL PROTECTED]:
On 3-mrt-08, at 18:43, Don Dailey wrote:
I base that logic on my observations that once the score goes below 10%
for Lazarus, it is losing. It's extremely rare that it salvages a game
once the score goes below even 20%.
In which case I could argue
Quoting Don Dailey [EMAIL PROTECTED]:
Just to make it clear, the case we want to fix is the case where many
bots are programmed to resign. Lazarus will resign when the score is
below 1% (and has remained so for a couple of moves in a row which is
probably just a superstition on my part to
Quoting steve uurtamo [EMAIL PROTECTED]:
cool. do you have any examples from a 19x19 game? that's what
i was referring to when i said that i've never seen an MC player
play out a ko fight.
Valkyria is unfortunately way to weak for 19x19. My argument is more
that in principle MC programs
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