Re: [gnugo-devel] Research

[Douglas Ridgway]

Hi Reona,

On Sat, 20 Nov 2004, Reona R Kumagai (address@hidden) wrote:

>  I am a Junior at Princeton University looking for a research topic on
> machine learning and Go. I was reading the task list posted on the
> GNUgo and found this to be intersting.
> 
> "Fuseki tuning by hand is difficult. People who are interested
>    in doing machine learning experiments with GNU Go could try
>    working with fuseki. This may be one of the areas with most
>    potential for substantial and reasonably quick improvements."
> 
> What kind of research has been done, and what kind of research do you
> think will be helpful in furthering computer go?

You might take a look at patterns/extract_fuseki with the statistics code
I've added recently, which was aimed at that comment. The idea is to
select a set of games played by GNU Go, collect statistics, and identify
whole-board patterns which do better or worse than the alternatives. What
to do then is a separate question, which may depend on things like the
opponents, the size and significance of the difference in outcome, as well
as possible reasons for the difference. So far, the only change has been
to deweight a 3-3 or 3-4 first move on a 9x9 board, but more is no doubt
possible.

There's also code and patterns for generating fuseki moves aside from the
whole board database, which might be interesting to look at. 

I believe there's also been some work on choosing large and strong opening
books for chess programs. I'm not familiar with this, but some concepts
may carry over.

doug.
address@hidden