It is true that MC-programs has a bias towards overconcentration. But...
1) A improvements to the simulations of MC-program as implemented by MoGo and
Valkyria does diminish the problem. In fact most of the strength of these
programs from doing that. I think it is next to possible to explicitly
Yes, we heard that argument for years in computer chess and it never
happened.
Do you have some kind of basis for believe that?
i wouldn't argue that future algorithms can't be time-doubled beyond
the existing skill level of people, just that the current evidence is weak
that we already
Note that professionals do not play perfect endgame, ...
Enough, apparently, that it separates a world champion from a
run-of-the-mill 9-dan.
Also, post-mortem analysis of pro games published in go magazines
routinely finds some game-result changing improvements in the endgame.
Yes, though
Been following this thread pretty closely and thought I would jump in
with a thought and try to find some common ground. I think there is
truth to be found in both sides of this argument.
Of course people improve with time and so do computers with certain
algorithms. The question is about
Direct link:
http://www.mimuw.edu.pl/~lew/download.php?file_no=8
Łukasz
On 1/22/07, Łukasz Lew [EMAIL PROTECTED] wrote:
Hi,
Few interesting things has happened so I decided to announce new version:
- bug-fix: komi was too big (1 point) so program as white tended to
loose by 0.5 point
-
On 21-jan-07, at 19:27, Don Dailey wrote:
not considering biological factors
which would cut into this a bit.
There was a time when there were no time-limits in Go, which was
abused by many players by turning a game into a stamina contest. I
believe this practice was abandoned when
On 1/22/07, Vlad Dumitrescu [EMAIL PROTECTED] wrote:
Hello Lukasz,
On 1/22/07, Łukasz Lew [EMAIL PROTECTED] wrote:
Few interesting things has happened so I decided to announce new version:
I have a few observations:
* in order to make libgoboard compile under cygwin I had to rename
const
Randomization of seed may not be a good idea. For some experiments it
is better to know the starting seed and keep it the same, for others,
like play against humans, randomization is probably preferable.
I would suggest having a runtime flag that can be set either way.
Cheers,
David
On
At 09:27 AM 1/22/2007, you wrote:
...
Don believes there is probably no difference and
states a rule: doubling thinking time = linear improvement in play.
i agree with this over some small range of powers of two.
..., as breaking the game into regions and doing
local reading and global
