> # One question: where _aya_ comes from or stands for? If my guess is
> correct, you are confusing Hiroshi, author of Aya, and I, Hideki,
> author of GGMC :). I'm sorry if I'm wrong.
I did. Sorry for the confusion. :(
Jonas
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computer-go mailing
Reminder - it's later today
In message <[EMAIL PROTECTED]>, Nick Wedd
<[EMAIL PROTECTED]> writes
Registration is now open for this Sunday's bot tournament. This will
use full-sized boards for both divisions. It will start at 16:00 GMT,
and take place in the Asian night, European evening, and
> From my observaion, mc chooses good moves if and only if the winning
> rate is near 50%. Once it gets loosing, it plays bad moves. Surely
> it's an illusion but it helps to prevent them.
If it's more important to avoid being too pessimistic (ie low estimated
winning rates), there are two wa
Petr Baudis wrote:
> The point here is to prevent the program from playing the "MC-hamete"
> moves that in most cases have no hope of working, but instead still aim
> at a close game and wait for some opponent's yose mistake. This closely
> matches human approach to the game as well - if you are co
Hideki Kato wrote:
> [EMAIL PROTECTED]: <[EMAIL PROTECTED]>:
>
>>> delta_komi = 10^(K * (number_of_empty_points / 400 - 1)),
>>> where K is 1 if winnig and is 2 if loosing. Also, if expected
>>> winning rate is between 45% and 65%, Komi is unmodified.
>>>
>> There's one thing I don't l
> I don't see that, but then again I am not a very strong player
> myself. What I notice is that it plays very "normal" until it's
> pretty obvious that it's losing, not just when it varies slightly from
> 50% but when it doesn't vary much from zero. However, it does play
> more desperately
>
> I don't like using the words "good" and "bad" when describing the
> quality of the moves because I try to use terminology that's more
> descriptive (although I fail miserably many times.)In a lost
> position how do you distinguish one move from another when they all
> lose? It sounds f
There is much high-level data to be found within the MC runs, such as
whether a group is alive or not, etc.
Now, I don't know if it is easy to inject it back within the
simulations.
Another approach (not excluding the first one) would be to gather much
lower-level data.
It's especially sad that t
David Fotland wrote:
>> I don't like using the words "good" and "bad" when describing the
>> quality of the moves because I try to use terminology that's more
>> descriptive (although I fail miserably many times.)In a lost
>> position how do you distinguish one move from another when they all
Actually, I think the solution to all of this is relatively simple.
When the programs go into the state where the moves are no longer
"cosmetically appealing" it's because all the moves lead to the same
result, whether it be wins or losses.
That being so, one solution is to impose a different m
Jonas Kahn wrote:
>> I don't see that, but then again I am not a very strong player
>> myself. What I notice is that it plays very "normal" until it's
>> pretty obvious that it's losing, not just when it varies slightly from
>> 50% but when it doesn't vary much from zero. However, it does
a few subtleties --
it's possible for a machine to play a perfect endgame, and my
guess is that machines will play perfect endgames before people
do, although most pros are excellent at the endgame.
counting ko threats and utilizing kos effectively is tricky in playouts --
kos can naturally exten
Mogo is already very strong at endgame and certainly plays perfectly near the
end of the game. The more advanced the program, the sooner it can play perfect
endgame.
But correct ko threats playing has nothing to do with the playout part : Since
it is a strategic concept that involves global unde
I think it is a very good and natural idea. I guess in the future, all MC
programs will have some kind of dynamic playout policies.
- Message d'origine
De : Jonas Kahn <[EMAIL PROTECTED]>
À : computer-go
Envoyé le : Dimanche, 2 Mars 2008, 19h43mn 29s
Objet : [computer-go] Tactical inf
i'm just saying (and perhaps i'm misunderstanding something here)
that lots of playout depth, and therefore lots of simulations are required
to see *any* advantage to playing out a ko.
s.
On Sun, Mar 2, 2008 at 3:17 PM, ivan dubois <[EMAIL PROTECTED]> wrote:
> Mogo is already very strong at endg
> But correct ko threats playing has nothing to do with the playout part :
> Since it is a strategic concept that involves global understanting, It is
> handled by the UCT tree part.
Yes and no.
Theoretically, that's the work of the UCT part. But, as Steve pointed
out, kos can go on for long. I
Ok, I think I see what you mean, but I am not sure I really agree.
As you say, this is related to horizon effect. I think current MC programs can
play ko quite well because they are trying do delay the outcome of losing the
ko, therefore they tend to play threats do gain time, just like human pl
the issue with ko is the order in which the ko threats are played,
which can only be successfully evaluated if the average playout
finishes the ko correctly.
s.
On Sun, Mar 2, 2008 at 4:56 PM, ivan dubois <[EMAIL PROTECTED]> wrote:
> Ok, I think I see what you mean, but I am not sure I really agr
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