On Sat, Nov 15, 2008 at 11:38:34PM +0100, [EMAIL PROTECTED] wrote:
> Being a computer scientist but new to go, i can grasp some of the theory.
> The question I was trying to get across was:
>
> In a game of self play, if both parties are employing only monte carlo,
> surely its not a good conceptu
On Sunday 16 November 2008, Heikki Levanto wrote:
> On Sat, Nov 15, 2008 at 11:38:34PM +0100, [EMAIL PROTECTED] wrote:
> > Being a computer scientist but new to go, i can grasp some of the theory.
> > The question I was trying to get across was:
> >
> > In a game of self play, if both parties are e
>> In a game of self play, if both parties are employing only monte
>> carlo, ... random simulations... wouldnt it be very weak...
>> ... and some playing around I am clearly mistaken because its works
>> quite well.
>Yes, it doesn't make sense but it does indeed seem to work :-).
Plain Monte-Carl
Hello Heikki,
Heikki Levanto: <[EMAIL PROTECTED]>:
>On Sat, Nov 15, 2008 at 11:38:34PM +0100, [EMAIL PROTECTED] wrote:
>> Being a computer scientist but new to go, i can grasp some of the theory.
>> The question I was trying to get across was:
>>
>> In a game of self play, if both parties are emp
On Sun, Nov 16, 2008 at 11:46:28AM +, D Gilder wrote:
> > This is the way I understand the random playouts: If, in a given position,
> > white is clearly ahead, he will win the game if both parts play perfect
> > moves. He is also likely to win if both parts play reasonably good moves
> > (say,
Quoting Hideki Kato <[EMAIL PROTECTED]>:
Heikki Levanto: <[EMAIL PROTECTED]>:
The way I understand it, modern Monte Carlo programs do not even try to
emulate a human player with a random player - obviously that would not work.
I believe CrazyStone's use of patterns does so and it seems
succes
On Sun, 16 Nov 2008, Claus Reinke wrote:
> ...
> better feeling for the game; personally, I don't like fast games(*), but
> ...
But there is this saying:
"Play quick, lose quick, learn quick!" :)
Thomas
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The random playouts or even heavy playouts are not intended to emulate
a human player. Heikki is exactly right.
It's a crude measurement of how good the position is. The moves in a
random playout are horrible and so are the moves in a heavy playout.
In fact, improving them arbitrarily will
I thought Valkyria does local search (ladders) during the playouts.
Many Faces is lighter on the playouts. I have 17 local 3x3 patterns, then
go to uniform random without filling eyes.
Against Gnugo 3.7.10 level 10 on 9x9, with 5000 playouts, I win 92%, so our
performance is similar. I'm doing
Yes, Valkyria does a lot of ladder reading as well. Actually "pattern
matching" in the case of Valkyria is a little unclear, it is a
decision trees where the leaves are often procedure calls that looks
at a larger portion of the board. The ladder code is called for
various reasons in the tr
On Nov 16, 2008, at 11:18 AM, "David Fotland" <[EMAIL PROTECTED]
games.com> wrote:
I thought Valkyria does local search (ladders) during the playouts.
Many Faces is lighter on the playouts. I have 17 local 3x3
patterns, then
go to uniform random without filling eyes.
No capture bias in
I think I added a small capture bias, but it didn't make much difference.
Sorry, I forgot that it isn't quite pure random. Before the uniform random,
if there is an enemy one liberty group on the board, with some small
probability, I capture it.
A pattern includes don't cares and is matched in
Some months ago I did several experiments with using tactics and
patterns in playouts. Generally I found a big boost in strength using
tactics. I also found a boost in strength using patterns but with a
severe diminishing return after a certain number and even becoming
detrimental when usin
So you say that: "...I'm observing that most of the increase in level
comes from the selection during exploration and only in small part
from the selection during simulation.", could you elaborate at all?
This is very interesting. That almost suggests it might be fruitful
to use the patterns in th
On 17-nov-08, at 02:42, George Dahl wrote:
So you say that: "...I'm observing that most of the increase in level
comes from the selection during exploration and only in small part
from the selection during simulation.", could you elaborate at all?
This is very interesting. That almost suggests
I look forward to hearing more! Happy testing.
- George
On Sun, Nov 16, 2008 at 11:53 PM, Mark Boon <[EMAIL PROTECTED]> wrote:
>
> On 17-nov-08, at 02:42, George Dahl wrote:
>
>> So you say that: "...I'm observing that most of the increase in level
>> comes from the selection during exploration a
It seems move selection in the playouts should be very random at first and more
deterministic toward the end of the playout. Has anyone tried that?
Mark Boon wrote:
On 17-nov-08, at 02:42, George Dahl wrote:
So you say that: "...I'm observing that most of the increase in level
comes from t
Yes, the best combination for my program, Antigo, is to use (somewhat) more
stochastic
moves for the first 5-9 ply.
I decided to look into this after noticing how surprisingly badly my heavy
playouts
did as part of AMAF without UCT/tree search. A more stochastic version of my
heavy
pla
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