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
On Fri, 2008-08-29 at 10:00 +0200, Magnus Persson wrote:
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
Don Dailey wrote:
Assuming a program
doesn't forfeit in stupid ways, they NEVER have bad days, wake up on
the wrong side of the bed, get in a fight with their spouse, get
inspired to play well on a particular day or depressed on another day.
It doesn't feel pain, or pity, or remorse. And
On Thu, 2008-08-28 at 09:38 +0200, Rémi Coulom wrote:
Don Dailey wrote:
I don't really believe the ELO model is very wrong. I only believe
it is a mathematical model that is somewhat flawed for chess and
presumable also for other games. Do you have an alternative that might
be more
On Thu, 2008-08-28 at 08:21 -0400, Michael Williams wrote:
Don Dailey wrote:
Assuming a program
doesn't forfeit in stupid ways, they NEVER have bad days, wake up on
the wrong side of the bed, get in a fight with their spouse, get
inspired to play well on a particular day or depressed
Oh yes, the graphs are still there:
http://cgos.boardspace.net/study/
http://cgos.boardspace.net/study/13/
- Don
On Thu, 2008-08-28 at 10:10 -0400, Don Dailey wrote:
On Thu, 2008-08-28 at 09:38 +0200, Rémi Coulom wrote:
Don Dailey wrote:
I don't really believe the ELO model is very
Regarding a rating system which provides more dimensions, may I suggest a test
suite of problems at different levels?
Convert life-and-death problems to solve this problem or lose the game
situations which can be properly appreciated by monte carlo programs, and make
a guesstimate of the elo
This was my post about multi-dimensional Elo:
http://www.mail-archive.com/computer-go@computer-go.org/msg06267.html
I have not tried it since that time.
Rémi
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On Thu, 2008-08-28 at 17:44 +0200, Rémi Coulom wrote:
This was my post about multi-dimensional Elo:
http://www.mail-archive.com/computer-go@computer-go.org/msg06267.html
I have not tried it since that time.
Wow, I can't believe I forgot about this one. It was less than a year
ago that you
you could use HMMs as long as you
didn't mind retraining (and thus starting your ratings
system over from scratch) every time you added or
subtracted a new player. it'd be relatively fast in any case.
s.
On Thu, Aug 28, 2008 at 11:44 AM, Rémi Coulom
[EMAIL PROTECTED] wrote:
This was my post
If you ever want to try, I can give you the data for cgos in compact
form that you can experiment with (one line per game - 2 names and 1
result + date) or you can simply extract them from the archived games.
- Don
On Thu, 2008-08-28 at 17:44 +0200, Rémi Coulom wrote:
This was my post about
this approach would also severely limit the number
of players that could be involved in the rating system,
since it would require manipulating an 2*(N choose 2)
matrix, where N is the number of players involved.
s.
On Thu, Aug 28, 2008 at 12:35 PM, steve uurtamo [EMAIL PROTECTED] wrote:
you
On Thu, 2008-08-28 at 08:37 -0700, terry mcintyre wrote:
Regarding a rating system which provides more dimensions, may I suggest a
test suite of problems at different levels?
Convert life-and-death problems to solve this problem or lose the game
situations which can be properly
out of curiosity, can you estimate the largest number of opponents
that all played each other a reasonable number of times? (i.e. what's
the largest subset of opponents and number of games that you
can choose so that everyone started playing everyone else in
the subset without anyone leaving for
Steve,
If you go here:
http://cgos.boardspace.net/9x9/digest.txt
http://cgos.boardspace.net/13x13/digest.txt
http://cgos.boardspace.net/19x19/digest.txt
you will get a compact digest of all games played that is up to date
within a few hours at any particular moment. With awk, sort,
On Thu, 2008-08-28 at 16:26 -0400, Don Dailey wrote:
Steve,
If you go here:
http://cgos.boardspace.net/9x9/digest.txt
http://cgos.boardspace.net/13x13/digest.txt
http://cgos.boardspace.net/19x19/digest.txt
you will get a compact digest of all games played that is up to
The scary strong Rybka program claims to be weak tactically. The
developers say that problem solving skill does not correlate strongly
with playing strength and they don't tune or care about that.
I've found the same thing for go. I have a large tactical problem set, and
I use it
What were the software improvements? Were they related to the code distributing
the work, or to the actual game playing/move selection code?
Jim
- Original Message
From: Robert Waite [EMAIL PROTECTED]
To: computer-go@computer-go.org
Sent: Wednesday, August 27, 2008 9:54:14 AM
You really can't conclude much about any mogo strength improvement from just
one game.
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Robert Waite
Sent: Wednesday, August 27, 2008 7:54 AM
To: computer-go@computer-go.org
Subject: [computer-go] yet a mogo vs human game
* -
In principle MoGo ought to be about a stone (or slightly more) weaker
with 1/5 the processing power, which is consistent with 2-3d against
Kim and 1-2d against the 6d.
I watched both games, and MoGo did seem stronger to me against Kim...
but then, I knew in advance the processing power in
On Wed, 2008-08-27 at 16:08 -0400, Robert Waite wrote:
* You really can't conclude much about any mogo strength improvement from just
* one game.
It is true that you can't make a conclusion.. but you can draw some
information
from two games. I would think it is statistically unlikely that
On Wed, 2008-08-27 at 13:20 -0700, Bob Hearn wrote:
In principle MoGo ought to be about a stone (or slightly more) weaker
with 1/5 the processing power, which is consistent with 2-3d against
Kim and 1-2d against the 6d.
I watched both games, and MoGo did seem stronger to me against
On Aug 27, 2008, at 2:48 PM, Don Dailey wrote:
On Wed, 2008-08-27 at 13:20 -0700, Bob Hearn wrote:
In principle MoGo ought to be about a stone (or slightly more) weaker
with 1/5 the processing power, which is consistent with 2-3d against
Kim and 1-2d against the 6d.
I thought a doubling was
Don Dailey wrote:
On Wed, 2008-08-27 at 14:56 -0700, Bob Hearn wrote:
The MoGo team has said that MoGo wins 62% of its games against a
baseline version when the processing power doubles. That's about
half
a stone (if you assume you can generalize to human opponents).
Yes, I believe
- Original Message
From: Rémi Coulom [EMAIL PROTECTED]
According to my experience with Go data, it is not possible to give the
value of one stone in terms of Elo ratings. For weak players, one stone
is a lot less than 100 Elo. For stronger players, it may be more.
Also, it is
On Thu, 2008-08-28 at 00:45 +0200, Rémi Coulom wrote:
Don Dailey wrote:
On Wed, 2008-08-27 at 14:56 -0700, Bob Hearn wrote:
The MoGo team has said that MoGo wins 62% of its games against a
baseline version when the processing power doubles. That's about
half
a stone (if you
On Aug 25, 2008, at 10:47 PM, Olivier Teytaud wrote:
Just for information, mogo will play in a few minutes (on Kgs /
computer-go) some games
against high level humans.
MogoTitan is playing 9x9 against nutngo ?
Christoph
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Yes, and then 19x19 with handicap.
On Aug 25, 2008, at 10:47 PM, Olivier Teytaud wrote:
Just for information, mogo will play in a few minutes (on Kgs /
computer-go) some games
against high level humans.
MogoTitan is playing 9x9 against nutngo ?
Christoph
More informations later, but we can already say that:
- the opponent is 6D
- MoGo was using 5% of Huygens (instead of 25% against Kim);
- there were some software improvements
- MoGo won 2 out of 3 games in 9x9 (even games)
- MoGo won with handicap 5 in 19x19 against the 6D player
- games can be
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