I've been messing around with where to apply heuristics. Candidates
include:
1) In the UCT tree, since this is earliest in each playout.
2) In the moves beyond the tree (heavy playouts), since this is where
most of the moves happen. Because this part is so speed-critical, ...
Remi (using
Darren Cook wrote:
I've been messing around with where to apply heuristics. Candidates
include:
1) In the UCT tree, since this is earliest in each playout.
2) In the moves beyond the tree (heavy playouts), since this is where
most of the moves happen. Because this part is so speed-critical, ...
Peter Drake wrote:
On Jun 6, 2007, at 2:41 PM, Rémi Coulom wrote:
Also, if you have a clever probability distribution, the range of
values for each move will be very large. For instance, here are two
3x3 shapes used by Crazy Stone (# to move):
O O #
# . .
# O #
Gamma = 143473;
. # #
.
Jacques Basaldúa wrote:
Rémi, are your values the result of learning in masters games?
Yes. I took data from a learning experiment based on very few games. So
there may be a little overfitting. Still, the ratio between the
strongest and the weakest patterns is always very big.
I'll run
This sounds a lot like the roulette wheel selection scheme used in
genetic algorithms. The idea is that each candidate has a different
slice of a roulette wheel, with better candidates getting bigger slices.
Peter Drake
http://www.lclark.edu/~drake/
On Jun 6, 2007, at 2:07 AM, Jacques
Álvaro Begué wrote:
Actually, John had a better idea to do this. In two words: binary
tree. The root represents the whole board, and it contains the sum of
the probabilities of all the points (you don't need to force this to
be 1, if you use non-normalized probabilities). This node points to
On 6/6/07, Rémi Coulom [EMAIL PROTECTED] wrote:
I wonder if other people had thought about this before...
Álvaro.
Yes, I did it in the beginning. But I found that it is faster to divide
by more than two. Currently, I keep the probability of the whole board,
each line, and each point. It is
I would be weary of using java.util.Random - it is not that random:
http://alife.co.uk/nonrandom/.
A drop in Mersenne Twister replacement for java.util.Random is available at
http://cs.gmu.edu/~sean/research/.
Cheers,
Graham.
On 05/06/07, Peter Drake [EMAIL PROTECTED] wrote:
Oddly, there
Jason House wrote:
On 6/6/07, *Rémi Coulom* [EMAIL PROTECTED]
mailto:[EMAIL PROTECTED] wrote:
I wonder if other people had thought about this before...
Álvaro.
Yes, I did it in the beginning. But I found that it is faster to divide
by more than two. Currently, I
Thanks for the tip. It does seem a bit faster (5% speedup of the
program overall), and I'm willing to accept the consensus that the
randomness is better.
Peter Drake
http://www.lclark.edu/~drake/
On Jun 6, 2007, at 2:15 PM, Graham Thomson wrote:
I would be weary of using java.util.Random
On Jun 6, 2007, at 2:41 PM, Rémi Coulom wrote:
Also, if you have a clever probability distribution, the range of
values for each move will be very large. For instance, here are two
3x3 shapes used by Crazy Stone (# to move):
O O #
# . .
# O #
Gamma = 143473;
. # #
. . .
. . .
Gamma
On Tue, 2007-06-05 at 10:23 -0700, Peter Drake wrote:
While there is a bias in theory, I suspect that you are right that it
is not significant in practice if you maintain a list of vacant points
(as Orego now does), because almost all vacant points are legal.
In any case, switching to your
On 6/5/07, Peter Drake [EMAIL PROTECTED] wrote:
On a multithreaded program like Orego (running on a multicore machine), it
moves the nontrivial random number generation out of the synchronized part
of the program and into the threads.
I'm surprised to hear this. Do you have a single random
But if you are taking the vacant points out it is probably not
too biased as you say.
But what I do is pretty fast. Always choose a random point but
keep shrinking the list. When a point is occupied move it out
of the way so it's never selected again. You have to do some
simple bookeeping -
Oddly, there doesn't seem to be much effect on speed whether I use a
single random number generator (i.e., instance of java.util.Random)
or one for each thread.
Peter Drake
http://www.lclark.edu/~drake/
On Jun 5, 2007, at 11:59 AM, Jason House wrote:
On 6/5/07, Peter Drake [EMAIL
On Tue, 2007-06-05 at 12:28 -0700, Peter Drake wrote:
Don't maintain the list of legal moves -- maintain the list of vacant
points (almost all of which are legal). When it's time to pick a move,
pick a random point in the list and iterate through checking each move
for legality. As soon as you
On Tue, 2007-06-05 at 15:58 -0400, Don Dailey wrote:
You might improve the bias by shuffling on the fly, perhaps when you
find a legal move in the un-occupied point section of the list you
could
do a swap with the first move and a random move. I'm wondering if
the
biased ordering of the
On Tue, 2007-06-05 at 13:12 -0700, Peter Drake wrote:
So I'm only temporarily maintaining a list of illegal but unoccupied
points - this list gets discarded as soon as a legal move is
tried.
Does that mean you have to regenerate the list every move?
I keep the list of un-occupied points -
On Jun 5, 2007, at 12:58 PM, Don Dailey wrote:
On Tue, 2007-06-05 at 12:28 -0700, Peter Drake wrote:
Don't maintain the list of legal moves -- maintain the list of vacant
points (almost all of which are legal). When it's time to pick a
move,
pick a random point in the list and iterate
-ansi -Wall -pedantic
Why not add -Werror so gcc rejects to compile code with warnings ?
Regards
Martin
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When writing C/C++ for multi-platform student assignments using gcc,
we always used the args:
-ansi -Wall -pedantic
Literally use the ANSI standard turn all warnings on and be
pedantic about warnings. This, of course, won't help with libraries
not being found.
cheers
stuart
Hello,
When writing C/C++ for multi-platform student assignments using gcc,
we always used the args:
-ansi -Wall -pedantic
Maybe it depends on the gcc versions, but I always use -Wall -W rather
than only -Wall. -W turns on (important) warnings which are not turned
on with only -Wall, and as
Hola, Álvaro:
Álvaro Begué wrote:
Could not compile libego is not a very helpful error message. What
exactly did the compiler complain about? My guess is that you don't
have the required boost libraries installed.
Yes. It must be that. I didn't know about boost libraries. Where can I
find
Lukasz Lew wrote:
Is libego too complicated? Do You have problems with compilation?
Or You are not comfortable with the GNU license? Any other reason?
I only wanted to compare performance ( and see what good ideas
you had ;-) ) but could not compile libego. Neither with Microsoft
Visual
On 5/30/07, Jacques Basaldúa [EMAIL PROTECTED] wrote:
Lukasz Lew wrote:
Is libego too complicated? Do You have problems with compilation?
Or You are not comfortable with the GNU license? Any other reason?
I only wanted to compare performance ( and see what good ideas
you had ;-) ) but
Álvaro Begué wrote:
At least for Windows programmers, providing a solution that
compiles with major IDEs would help. I assume what you do is
standard in Linux, but the things the compiler did not understand
neither did I, and I could not find the time for googleing.
With 1.08 version of lego
On 5/30/07, Berk Ozbozkurt [EMAIL PROTECTED] wrote:
Álvaro Begué wrote:
At least for Windows programmers, providing a solution that
compiles with major IDEs would help. I assume what you do is
standard in Linux, but the things the compiler did not understand
neither did I, and I could not
On Sun, 27 May 2007, ?ukasz Lew wrote:
Jason, can You tell me why You don't want to use libego instead?
Actually this is open question to all comp-go readers.
Is libego too complicated? Do You have problems with compilation?
Or You are not comfortable with the GNU license? Any other reason?
I
But I remember thinking that it might still be useful for evaluation. I
remember thinking that that if you compared pseudo liberties to real
liberties it might tell you something. If the ratio was high (a lot
more pseudo liberties) it might indicate that the liberties are easy to
protect. But
Hi,
I've tested many approaches, and the one I implemented is clearly the best.
The bias that Peter Drake talks about is negligible and doesn't have a
noticeable impact
on playout results.
(and uniformity of playout isn't something to fight for in MC Go)
Jason, can You tell me why You don't
i'd need to write a C interface for it, then try to maintain compatibility
through new releases. (AKA i'd effectively end up rewriting it). it might
seem like less of a burden for me to just write my code in C++, but
i guess i'm just a caveman who is stuck in his old ways and would rather
Yeah, I suffer from this, too. (There's also the fact that using
someone else's code would disqualify you from the formal division of
the KGS tournaments.)
Here's a heroic tale of not-invented-here syndrome for your amusement:
http://worsethanfailure.com/Articles/slammerSCR.aspx
Peter
Here is what I do, don't know if it's best
Basically you want a list of empty points, since most of them are legal.
When I apply a move to the board I then do any needed legality
testing.
At the beginning I start with a list of ALL points on the board. When
a non-empty point is
I'm a language caveman too then. I really avoid C++ even though I
learned the basics long ago. I really hate it. It's not like I'm
an old dog that can't learn new tricks - I have experimented and
explored many computer languages and I am versatile in many.
It's one of those languages
On Sun, 2007-05-27 at 13:21 -0400, Jason House wrote:
As I get into the home stretch of rewriting the core of my bot, I want
to add a monte carlo player. I've realized that picking a random move
to play is non-trivial since it's such a key element in playout speed.
An array of
?ukasz Lew wrote:
Jason, can You tell me why You don't want to use libego instead?
Actually this is open question to all comp-go readers.
Is libego too complicated? Do You have problems with compilation?
Or You are not comfortable with the GNU license? Any other reason?
I probably have a lot
I struggled with unto a lot, too. In the current version of Orego,
there is no undo, just a way to copy a board relatively quickly. This
falls under keep the common case fast again: you only undo once
per playout, so it's faster to make a copy.
(For the real board, where actual games moves
Darren Cook wrote:
Jason House also mentioned hard coding to a set board size, I think
libego can be used at least up to 19x19, just by changing the
board_size setting in board.cpp (it also supports hexagonal boards).
Or did you mean being able to make one binary for all board sizes? I
feel that
On Sun, 2007-05-27 at 19:31 -0400, [EMAIL PROTECTED] wrote:
If I had it to do over again, knowing what I know now, I would not spend a
lot of time optimizing random games. These optimizations don't make much
difference for heavy playouts and heavy playouts are better.
- Dave Hillis
I remember that conversation and the negative response. But to be fair
to the ones who were negative, you presented this as an evaluation
feature that could be calculated quickly, not as a pure performance
optimization. The negative response was in response to the suggestion
that it might be
Don Dailey wrote:
I remember that conversation and the negative response. But to be fair
to the ones who were negative, you presented this as an evaluation
feature that could be calculated quickly, not as a pure performance
optimization. The negative response was in response to the
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