Hi,
On 12/22/06, Stuart A. Yeates [EMAIL PROTECTED] wrote:
On 12/21/06, Jacques Basaldúa [EMAIL PROTECTED] wrote:
Handicap play is a *different* problem.
The rules of go include rules for handicapping.
It seems to me that this implies that a complete solution for the game of go
must include
On 12/11/06, [EMAIL PROTECTED] [EMAIL PROTECTED] wrote:
Hello all.
I've been lurking on the list for a few years now. In amongst the usual
musings on the meaning of AI and social justice, etc., there's been a sharp
increase in the amount of useful information posted here of late. I'll try
to
Hi,
I'm about to finish the development of libgoboard,
if anybody has any more suggestions / bug reports, please send them :)
In this version we have new:
- array of empty intersections build in board (slowdown of few percent), but
very convenient for search algorithms.
- mercy rule (thank
Hi Don,
On 12/22/06, Don Dailey [EMAIL PROTECTED] wrote:
It's easy to adapt monte carlo programs to have the goal of trying to
win as much space or territory as possible but many of us have studied
this as see that it seriously weakens monte carlo programs.
My (jokingly serious) point was
This is the strategy that one uses even in even games, right? One
plays what one thinks is best given the position, and if the
opponent's reply is less than optimal one tries to punish it (with
various degrees of success, but that's another issue :-))
It's the strategy in even games, but not
Hi Steve,
What you fail to take into considerations is that a monte/carlo
player may ruin it's chances before the weaker player has a
chance to play a bad move. The monte carlo player sees all
moves as losing and will play almost randomly.
In botnoids game against mogo, once mogo achieved
a
Don Dailey wrote:
Hi Steve,
What you fail to take into considerations is that a monte/carlo
player may ruin it's chances before the weaker player has a
chance to play a bad move. The monte carlo player sees all
moves as losing and will play almost randomly.
I don't agree. Here is the
Thanks for sending the statistics. I'll try them out later on my
programs too.
There is only 1 way to resolve this - maybe we should test it out
on a 19x19 handicap server. We can play a few weeks and then take
a look at the statistics later. I predict that gnugo will perform
better on
Quoting [EMAIL PROTECTED]:
on 9x9 boards. To make a long story short, I didn't see any evidence
that this algorithm is fundamentally disadvantaged in handicap games.
In fact, I agree with Remi's view that it is particularly *well*
suited to handicap games compared to territory based
There's also the small issue of the compensation given to white
because of the extra black stones on the board. Setting a modified
komi would break (MC-)programs with an internal rule for it. Not
setting it would break those who does not use that rule.
How is this compensation handled by the
I'm trying to figure this out. If you get a 9 stone handicap, you have
to give back those 9 stones? So a 9 stone handicap is not quite as
much
as it seems although it's still pretty good.
- Don
On Fri, 2006-12-22 at 21:24 +0100, Christian Nilsson wrote:
There's also the small issue of
Yes, in chinese rules you need to compensate white for the extra area
you gain from the actual stones. The handicap is only meant to be the
extra strength/stability.
One can of course ignore this for the server. I just wanted to make
sure all programs use the same rules. I don't know what the
Yes, in Chinese rules you need to compensate white for the extra area
you gain from the actual stones. The handicap is only meant to be the
extra strength/stability.
To be slightly more specific, the extra compensation is specific to
area scoring rule systems. In a game with only two passes,
My reading of http://homepages.cwi.nl/~tromp/go.html is that komi is only
supported among equal players, as agreed upon. However, this goes against the
practice in Chinese and Ing rulesets, where white does recieve a komi to
counterbalance the scoring of the additional stones placed by black.
So really, what I want to be able to do is:
1. Use the ELO rating system.
2. Determine how many ELO points 1 stone handicap is worth.
3. 2 stones are worth
4. 3 stones are worth,
etc.
When two players are matched, the server gives the
Le vendredi 22 décembre 2006 21:44, Don Dailey a écrit :
[...]
I still have a hard time believing that the system scales very well
across a 9 kyu range.
Handicap system works incredibly well, from very weak kyu to strong dan.
Moreover, the problem of the black players are the same whatever his
16 matches
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