[Computer-go] KGS tournament rules

Nick Wedd maproom at gmail.com
Thu Jun 4 13:56:12 PDT 2015

I have been asked

Your page [ http://www.weddslist.com/kgs/rules.html ] says:
> All the code in it that is in any way involved in move-generation (i.e.
>> anything that causes the program to prefer one move to another) or position
>> evaluation must be unique among the entrants. Code that is involved only in
>> non-essential parts of the program, such as input/output, or scoring the
>> position after the game is over, need not be unique. If two or more people
>> want to submit programs containing the same code, then the author of that
>> code shall decide which may enter.
> Would it be acceptable for me to use a (non-Go-specific) neural network
> package that I didn't write?

My immediate inclination is to say "Yes. It's like using a compiler that
you didn't write."  But
I fear it may be more complicated than that.

For now, the rule is that if you enter a KGS bot tournament using a neural
net that you did not write, your entry will be accepted, buy you must
specify what neural net you are using.

But I would like to discuss the issue, and accept the consensus of this
list.  I have never used a neural net, and my understanding of how they
work is close to zero.  I naively imagine it goes like this:
  1.  You obtain a neural net, by buying one, downloading a free one, or
getting one from a colleague.
  2.  You install it on your computer.
  3.  You configure it by setting some parameters.
  4.  You specify how its board state representation will work (I have very
little idea about this).
  5.  You train it, maybe by feeding it a large database of professional
  6.  You test the results. Quite likely you realise it hasn't gone well,
and redo from step 3.
  7. You add a harness that attaches it to kgsGtp, and maybe to some other

I look forward to becoming better informed.  I know that if someone writes
a praiseworthy program in say C, the creator of his C compiler will deserve
and expect none of the credit. I suspect things may be different with
neural nets.

Nick Wedd      maproom at gmail.com
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