[Computer-go] KGS tournament rules

Detlef Schmicker ds2 at physik.de
Thu Jun 4 14:20:25 PDT 2015

Hash: SHA1

Oakfoam uses caffe library.I did not ask, as I considered it the same
as using e.g. boost lihrary to not write special kind of maps, you do
not want to write your self.

Of cause the net definition and training is our own. Most of the code
would be linear algebra, if you would write it yourself, and you would
most probably use a library for this....


Am 04.06.2015 um 22:56 schrieb Nick Wedd:
> 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 games. 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 programs.
> 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
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