I suspect that even with a similarly large training sample for
initialization that AlphaGo would suffer a major reduction in apparent
skill level. The CNN would require many more layers of convolution;
the valuation of positions would be much more uncertain; play in the
corner, edges, and center
From the website http://www.gokgs.com/tournInfo.jsp?id=380 and the fact
that it hasn't started, I deduce that it starts at 1500 GMT, or about 40
minutes time.
On Sun, 2008-05-04 at 11:00 +0100, Nick Wedd wrote:
Reminder - it starts in a few hours (13:00 GMT), five hours after the
time of
I think that the original description of the position should have said
'killable' rather than 'dead', and that David missed the fact that
it is White to move.
At 08:06 27/03/2008, Hideki wrote:
David Fotland: [EMAIL PROTECTED]:
I just looked at this position and it looks like a win for black
This is very cool. As of 261 games played, I find it very difficult to
guess whether the mogo curve is beginning to dramatically flatten, or
will continue to rise steeply.
I have a few questions.
I can't see the cross table, I guess you haven't put it up yet?
How do you decide the pairings?
At 02:58 28/07/2007, Arend wrote:
On 7/26/07, chrilly
mailto:[EMAIL PROTECTED][EMAIL PROTECTED] wrote:
This is a remarkable result. I think poker is more difficult than Go and of
course chess.
I am as surprised by this statement as everyone else. Of course you
have to develop some mixed
At 18:20 26/07/2007, Jeff Nowakowski wrote:
On Thu, 2007-07-26 at 18:14 +0200, chrilly wrote:
Chess/Go... can be played in an autistic way. There is no need for an
opponent model.
Ah, an opponent model. Where's the poision?
http://www.imdb.com/title/tt0093779/quotes#qt0250635
Too much
At 12:42 28/07/2007, you wrote:
At 02:58 28/07/2007, Arend wrote:
On 7/26/07, chrilly
mailto:[EMAIL PROTECTED][EMAIL PROTECTED] wrote:
This is a remarkable result. I think poker is more difficult than Go and of
course chess.
I am as surprised by this statement as everyone else. Of course
Yes. This number is strongly dependent on strength and board size I
think. Very roughly speaking, you can argue as follows
1) in a 9x9 game, the weaker player has only 1/4 as many moves in
which to throw away the handicap advantage (compared to 19x19).
2) weak players lose so many points
At 21:54 08/07/2007, you wrote:
I don't have such algorithm, you can count legal positions like:
http://www.lysator.liu.se/~gunnar/legal.pike.txt
Modifying it could provide some way select random position atleast
for small boards. Ported that for java but not studied much of it
yet,
It might be worth asking the administrators of some go servers if
they would be prepared to give you copies of some games.
At 17:09 06/07/2007, you wrote:
I will play with Suzie at the forthcoming European Go championship
in Villach/Austria some 9x9 demonstration matches against everybody
It isn't a very good article in my opinion, but for what it's worth.
http://www.timesonline.co.uk/tol/comment/columnists/ben_macintyre/article2002699.ece
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There are multiple possible definitions of what it means for a player
to be the same strength on two different sized boards. It is impossible
to pit a 9x9 player against a 19x19 player. If two people
use different definitions of 'same strength', they are bound to disagree
about which size
as well. Or maybe Chrilly will make a monster
go machine even before that.
Could somebody comment please on the likely usefulness of massively parallel
machines to UCT-like algorithms.
Thanks again.
Tom.
At 21:12 10/04/2007, you wrote:
Hello,
2007/4/6, Tom Cooper
mailto:[EMAIL PROTECTED][EMAIL
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
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
My guess is that the complexity of achieving a fixed standard of play
(eg 1 dan) using a global alpha-beta or MC search is an exponential
function of the board size. For this guess, I exclude algorithms
that have a tactical or local component. If this guess is correct
then, even if Moore's
I agree. The feel of sensei's and wikipedia are completely different.
Most of the content on sensei's is too informal for wikipedia, and I
think it would get deleted if it was put there, despite this content
being very worthwhile. On the other hand,
wikipedia is the ideal place for a short
At 16:20 09/01/2007, you wrote:
i'd like to follow this up by saying that i'm interested
to see if anyone has compared winning percentage
in the following two situations:
i) maximize probability of win
ii) maximize probability of win until p_win 1-eps, then maximize
total score among all
At 23:17 03/01/2007, Don wrote:
David,
I thought of another way to put it which I think, in a way,
defines the difference in the rule-sets.
You are playing a game, and you think the opponent group
is dead. But you are not 100 percent sure.
What do you do? Chinese puts the emphasis on the
At 01:54 23/10/2006, you wrote:
There was a posting on this list with an example of a (contrived?)
situation where sacrificing a pass-alive group is appropriate, in order to
win a ko that is more valuable. Is even #1 100% admissible?
Weston
I must have missed this, and find it
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