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Re: [Bug-gnubg] User training of the Neural Nets

From: Øystein Johansen
Subject: Re: [Bug-gnubg] User training of the Neural Nets
Date: Wed, 23 Aug 2006 20:42:30 +0200
User-agent: Mozilla Thunderbird 1.0.6 (Windows/20050716)

Christian Anthon wrote:
> Okay then what level of programming skills would be needed and what
> should a programmer do?

1. Get the gnubg-nn code
   cvs -d:something:blah co gnubg-nn

2. make it compile
   If I remeber correctly it was:
   cd py
   gmake safe

   I believe there is some documentation on how to compile it.
   (Maybe a linux system makes it easier ?)

3. Before you start training anything:
   Steal the neural net evaluation code from gnubg, the code
   that uses SSE, and apply it to the code ing gnubg-nn.
   This step will save you a lot of time in the traing.
   (commit the changes back to the cvs)

4. Get the reference databases and the neural nets. It's on
   a ftp somewhere. I'll find the address when you need it.

5. Use the training scrips provided.
   train.py - trains a net
   buildnet.py - builds a net from scratch... really slow.
   getth.py - finds post that eval mismatch from n-ply to 0-ply
   referr.py - finds the error of a new breeded net against the
   reference database.

Here's where I stranded... It worked it worked! I could breed
new nets, but none of the nets I trained was significantly
better than the original onem no matter how long I trained.

6. A programmer can now try out different things, like further
   splitting of neural nets, or altering the inputs, or guessing
   other algorithms thar might work.

   Look at the different hand crafted inputs, can anyone be
   removed? Can anything be added? I believe there is code to
   dynamically add and remove nn inputs. If you add a input
   make sure you add a new 'concept' and not just something
   that's linearly depending on some other inputs.

I would love to see someone taking the training further.


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