[Computer-go] Recursive Neural Networks

Brian Sheppard sheppardco at aol.com
Wed Jan 23 12:00:42 PST 2013

The results that they are reporting don't seem state of the art at all.
E.g., they report that the top-ranked move from their neural net has a 10%
chance of matching a pro move on a 19x19 board.

My impression is that you can get better prediction accuracy just by using
the distance to the last opponent's move.

And if you use a large-scale pattern approach (e.g., Remi's work), then you
can predict over 40% and maybe up to 50% of pro moves.

Am I remembering this correctly?

-----Original Message-----
From: computer-go-bounces at dvandva.org
[mailto:computer-go-bounces at dvandva.org] On Behalf Of Mark Boon
Sent: Wednesday, January 23, 2013 2:45 PM
To: computer-go at dvandva.org
Subject: Re: [Computer-go] Recursive Neural Networks

Sorry, never mind. Next time I'll Google the title-author combination
before bothering anyone else, rather than after.


On Wed, Jan 23, 2013 at 9:36 AM, Mark Boon <tesujisoftware at gmail.com> wrote:
> OK, this is a bit of a cheapskate question.
> For a project I'm currently working on I'm considering looking into
> recursive neural networks. I bumped into the following article
> describing a project that used them to make a Go playing program:
> http://www.ncbi.nlm.nih.gov/pubmed/18420381
> I figure that even though I'm not going to use it for Go, being
> familiar with computer Go may make it easier for me to understand. But
> it costs $31.50 to download the article. I'm balking at the cost
> because a) I think these type of articles should actually be free to
> access and b) I've always been very skeptical this type of approach
> would work for Go so it may actually be a completely useless article
> at that.
> So I was wondering if anyone was aware of the article and could tell
> me whether it's worth even a buck, let alone thirty-one of them, to
> download it.
> Mark
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