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 h
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 giv
I'm glad you bring it up.
>From the same site, it appears there is no standard way of handling
this.
I will look to see what Tromp/Taylor says if anything.
It would be nice if we could simple equate handicap with ELO points, I
think it would be more accurate. We may find that 1 stone per kyu
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. On
In message <[EMAIL PROTECTED]>, Don
Dailey <[EMAIL PROTECTED]> writes
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.
You might want a Chinese-rules ha
>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 passe
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
tro
I'm wondering if the kyu system is screwed up without the compensation.
I still have a hard time believing that the system scales very well
across
a 9 kyu range. Would the extra compensation make the extreme handicaps
work better?
- Don
On Fri, 2006-12-22 at 13:36 -0700, Markus Enzenberger w
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 t
On Friday 22 December 2006 13:24, Christian Nilsson wrote:
> How is this compensation handled by the various programs on cgos, if at
> all?
>
> Check http://www.britgo.org/rules/compare.html#comp if you don't know
> what I'm talking about..
is there any logical explanation for this rule? I mean, W
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 vari
Ok,
Well I'm inclined to go with the majority which seems to have turned
around
from the last time I polled.
Now the question: How to set it up?
Here are the options:
1. Use GTP handicap commands to set up game.
2. Send the appropriate pass commands to get the initial setup
to acc
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 algorithms
I would like to see handicap games on CGOS.
AntIgo-4, playing on CGOS, uses MC/UCT and considers only win vs. loss,
ignoring margin of victory. I used a faster, dumber version of it to play a
number of handicap games against even weaker engines on 9x9 boards. To make a
long story s
Le vendredi 22 décembre 2006 17:25, Rémi Coulom a écrit :
> Here is the winning percentage I get with Crazy Stone at
> various handicaps, with a komi of 0.5, over 1 random simulations:
>
> 9 Stones: 0.74
> 8 Stones: 0.73
> 7 Stones: 0.69
> 6 Stones: 0.67
> 5 Stones: 0.63
> 4 Stones: 0.61
> 3
I think as a test, I would go with the full handicap system, I would
just refuse to match players that need more than 9 stones. I can
always cut it back to 4 or 6 later.
Why don't we view it as an experiment to gather a lot of statistics.
I can change back to ELO later.
The only question, and
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 handi
>I personally think small handicaps in 19x19 might be reasonable
because
>I think playing good moves is still a dominant factor - at least at
the
>levels our programs can handle. I would be reluctant to go beyond a
>few stones. I don't know what a good number is, but I'll take a
>somewhat
>e
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 winning
what i'm saying is that monte carlo is not
evaluating the game-theoretical value of the
board. what it is doing is looking for best
moves with respect to the function: "maximize
probability of win". probability of win is
not zero at the start, even with 6h. it is
lower than without handi, but no
Le vendredi 22 décembre 2006 16:03, Don Dailey a écrit :
> So it becomes far more important to play the opponent, not the board.
> All your hopes and dreams depend on your opponent, not the brilliancy
> of your moves (all of which lose.)
This is a problem of knowledge and estimation. In the beginn
Le vendredi 22 décembre 2006 16:21, Don Dailey a écrit :
> Hi Steve,
>
>
> In a high handicap game, a monte carlo program is
> likely to play the first few move randomly. Statistically
> they won't be able to see how C3 is any better than A19
> and so they will inadvertently give the weaker opp
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 "
Le vendredi 22 décembre 2006 14:50, Don Dailey a écrit :
[...]
> It seems that playing the best move possible (best in the sense of
> maximizing your territory gain) is not the best strategy when playing
> a handicap game. You literally have to play foolishly in order to
> dupe your opponent into
> 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 n
> IMHO if I give handicap it is because the other
> player is weaker, so I
> don't *have* to play foolishly - he will make
> mistakes that I can see
> and exploit. If I still can't win, it means the
> handicap should be
> lowered...
and any go program would operate the same way.
it would look hope
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 th
Vlad and Stuart,
I'm not completely closed on this issue - but there is lot going
against it
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
Hi
During kgs slow tournament we discussed about 7 groups
and the proverb "6 groups, one die"
I find the reference: Black has 7 groups and lose by 0.5
http://senseis.xmp.net/?NotSoMagnificentSeven
Alain
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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 to
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,
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 includ
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 the ability to play such games.
cheers
stuart
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