Overall, it's a good read.
Nitpicks:
• The scalability graphs need to be clearer. Maybe add a caption or
change the single-threaded label? I looked at the graphs first and
took a bit to figure out why "single-threaded" outperformed all else.
• The RAVE section wasn't all too clear. I think
Dear Isaac,
I'm about to work on heavy playouts, and I'm not sure how to choose
a move
during the playout. I intend to have weights for various features. I
thought
about 3 versions:
1. In a position, calculate all the weights and the total weight.
Then, play
one move i with the probab
2009/5/1 Brian Sheppard :
> In reading Sylvain Gelly's thesis, it seemed that incorporating a prior
> estimate of winning percentage is
> very important to the practical strength of Mogo.
>
> E.g., with 1 trials, Mogo achieved 2110 rating on CGOS, whereas my
> program attempts to
> reproduce ex
You have the most control with option 1. You can implement this fast
by keeping the sum of the weights for each row and for the total
board. You then "roll" a number between 0 and total_weight, and
advance through the rows subtracting the probability of each row until
you would cross 0, then go alo
Hello,
I'm about to work on heavy playouts, and I'm not sure how to choose a move
during the playout. I intend to have weights for various features. I thought
about 3 versions:
1. In a position, calculate all the weights and the total weight. Then, play
one move i with the probability weight_i/to
Hi Martin,
thanks for the information and the report.
In the abstract you write
"...Fuego includes a Go engine with a playing
strength that is competitive with the top
programs in 9x9 Go, ..."
I want to support this claim. Over the weekend
I had the fun to watch some free 9x9 games of
Fuego on
Our technical report describing the Fuego framework is now available on
http://www.cs.ualberta.ca/research/techreports/2009/TR09-08.php
I will probably make at least one more revision, so all feedback and
suggestions are welcome.
Thank you
Martin
_
Hi,
We used alpha=0.1. There may well be a better setting of alpha, but
this appeared to work nicely in our experiments.
-Dave
On 3-May-09, at 2:01 AM, elife wrote:
Hi Dave,
In your experiments what's the constant value alpha you set?
Thanks.
2009/5/1 David Silver :
Yes, in our experi
And just in case, here are some alternate links to the same files:
* MailArchive04052003.txt
http://www.filefactory.com/file/agf0d17/n/MailArchive04052003_txt
* MailArchive04052003.zip
http://www.filefactory.com/file/agf0dh4/n/MailArchive04052003_zip
* MailArchive0405
Michael Williams wrote:
> Michael Williams wrote:
>> See the April 30 2009 posting: http://www.tobiaspreis.de/
>>
>
>
> The CUDA SDK also comes with a sample called "Monte-Carlo Option Pricing"
I don't think there is much more relevance to Go than "it also uses
random numbers somewhere".
--
Here's a link to the archives of the computer go mailing list from 1993 - 2003
all in one file:
(available in zip, 7-zip and uncompressed)
http://www.mediafire.com/?sharekey=5e8b5601844d16558d78a0e5552916099b61fa34587d11e9c95965eaa7bc68bc
Ben Shoemaker.
- Original Message
From: Darr
Michael Williams wrote:
See the April 30 2009 posting: http://www.tobiaspreis.de/
The CUDA SDK also comes with a sample called "Monte-Carlo Option Pricing"
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