Re: [computer-go] Learning and Go

[Max Laager <max.laager@xxxxxxx>]

Hello
Im new to this list
I do a semestre project In computer science
on evoling a neural network so that it plays go...

> Hello all,
>
> I have written a neural Go program(in matlab) for a class, unfortunately I
> do not have statistical results other than it beat a random player 19X19.
>
> I am planning a decision tree program to "Learn" to play go.  My reasoning
> for choosing decision trees, being that information lead effects are very
> important in the opening, decision trees are fast to evaluate, and can
> eliminate irrelavant data.
>
> I also have the personal goal of learning to play go, so I would be
> interested in learning the results of the decision tree even if it does
> not play go well.  I think one of the interesting facts in the world of
> computer chess, is that the professionals started using computers to
> train, even before computers were winning.
>
> The first question that I had was if I should take advantage of symmetry,
> which is important when choosing data structures while parsing files.
> Does any one know of freely available C sgf libraries?

Yes shure Gnugo is Gpl and has a nice sgf reader...

>
> While with a 9x9 board there is a problem with insufficient data, which
> most learning algorithms are specialized for, the 19x19 board has much
> more data available, in fact maybe too much data.  I think I would choose
> to train my algorithm on an unseen example rather than a rotated version
> of another.  By the way FFT's are not rotation invariant.
>
> (Assuming Laziness is a virtue) Any suggestions, pointers to file parsing
> code(in C/C++, not matlab), or information about decision tree
> architectures which have already been attempted would be appreciated.
> Thank you all in advance!
>
> Sincerely,
>
> Robin Kramer
>
>
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