Le dimanche 8 avril 2007 03:05, Don Dailey a écrit :
A few weeks ago I announced that I was doing a long term
scalability study with computer go on 9x9 boards.
I have constructed a graph of the results so far:
http://greencheeks.homelinux.org:8015/~drd/public/study.jpg
Thanks for this
Paper 1 in the list below states:
Numbers were originally implemented in Lisp I as a list of atoms.
and the Lisp 1.5 manual states: Arithmetic in Lisp 1.5 is new
Could you give an example how the number 3 was implemented in Lisp-1 and how
2+1?
So far I have found only this remarks but not
Thanks dons for producing these fascinating results. I hope that
when you have finished the study, you will show us not just this
graph, but also the game results (number of wins) that it is
derived from.
At 02:05 08/04/2007, you wrote:
A few weeks ago I announced that I was doing a long term
According these results the slope is considerable greater than in chess. In
the classical experiment of Ken Thompons searching 1 ply deeper is worth
about 200 Elo. 1 ply corresponds to 5-6 times longer/faster. In 9x9 already
a factor of 2 gives the same improvement. This is really remarkable.
The discussion here http://senseis.xmp.net/?EloRating suggests that
the difference between beginners and top players in go is about 3000
ELO on a 19x19 board. This difference is very dependent on the board
size. I can
think of a naive argument that this difference should scale linearly
with
On Sun, 2007-04-08 at 09:56 +0200, Chrilly wrote:
Is it just enough to make a 2 million playouts version
to beat the top-Dans in 9x9? Is it that easy?
Of course the ELO numbers are arbitrary. I assigned GnuGo 3.7.9
a level of 2000 but on CGOS it is 1800.But CGOS numbers are
arbitrary
On Sun, 2007-04-08 at 09:36 +0100, Tom Cooper wrote:
Thanks dons for producing these fascinating results. I hope that
when you have finished the study, you will show us not just this
graph, but also the game results (number of wins) that it is
derived from.
I have all games and all data if
On Sun, 2007-04-08 at 11:24 +0200, Heikki Levanto wrote:
In fact this is how beginners think about the game. It doesn't
seem to me like a good learning aid to try to get the computers
to emulate the losing strategy weaker players use.
Weaker players can not estimate the score until
On Sun, 2007-04-08 at 14:44 +0200, Heikki Levanto wrote:
Aren't you being a bit optimistic here? It is quite conceivable that
the
curves will flatten out and reach a maximum level somewhat below
perfect
play. I don't see how we can predict the difference between them at
that
time.
UCT has
On Sun, Apr 08, 2007 at 08:48:03AM -0400, Don Dailey wrote:
On Sun, 2007-04-08 at 11:24 +0200, Heikki Levanto wrote:
Weaker players can not estimate the score until very late in the game.
Not with enough precision, anyway. Thus, most of the time they have no
idea if they are winning or
The question here is not about UCT(yes, it gaves the same rusults as
alpha-beta). It's about MC scoring. It has not been proved that MC score will
generate the optimum play with large enough simulation.
Now the best super computer uses about 500,000 CPUs, which is 2 to the 18th
power of
On Sun, 2007-04-08 at 18:11 +0200, Edward de Grijs wrote:
Hello Don,
A few weeks ago I announced that I was doing a long term
scalability study with computer go on 9x9 boards.
I have constructed a graph of the results so far:
Your work and insight keeps on amazing me.
If I understand
I'm not really fanatic about this either way. If I knew how to
easily fix this, I probably would provide a mode to make it
work either way.
I see it as aesthetically MORE pleasing when the program appears
to be playing stupid, but then you realize that YOU are the one
that doesn't
On Sun, 2007-04-08 at 10:09 -0400, [EMAIL PROTECTED] wrote:
The question here is not about UCT(yes, it gaves the same rusults as
alpha-beta). It's about MC scoring. It has not been proved that MC
score will generate the optimum play with large enough simulation.
MC is obviously wrong as an
Just a warning -
Tomorrow, I'm taking the old CGOS down and replacing it with
the NEW cgos.
Also, the CGOS test I'm running from my home computer will
go away. So the 2 minute server will also go away!
The new cgos on boardspace will be 5 minute time control
instead of the previous 10
I think you are right, because MC score becomes precise when only a few
available moves left. However, do you search to the depth of the end of the
game, or to the extent that MC score becomes precise?
-Original Message-
From: [EMAIL PROTECTED]
To: [EMAIL PROTECTED]
Cc:
Don Dailey wrote:
I have this idea that perhaps a good evaluation function could
replace the play-out portion of the UCT programs.
I thought about something similar but only for initializing the
counters: introduce 10 fake playouts and estimate the number of
wins by a function returning
I have this idea that perhaps a good evaluation function could
replace the play-out portion of the UCT programs.
I thought about something similar but only for initializing the
counters: introduce 10 fake playouts and estimate the number of
wins by a function returning something in [0, 10].
On 08/04/07, Jacques Basaldúa [EMAIL PROTECTED] wrote:
I will try to explain it better:
What had puzzled me until recently is how to combine two facts:
a. As Jason says, A single MC playout corresponds to a Bernoulli
trial with probability p and therefore, p-hat is distributed as a binomial
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