[Computer-go] Mastering the Game of Go with Deep Neural Networks and Tree Search (value network)

Álvaro Begué alvaro.begue at gmail.com
Thu Feb 4 10:33:42 PST 2016


I re-read the relevant section and I agree with you. Sorry for adding noise
to the conversation.

Álvaro.







On Thu, Feb 4, 2016 at 12:21 PM, Detlef Schmicker <ds2 at physik.de> wrote:

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> Thanks for the response, I do not refer to the finaly used data set:
> in the referred chapter they state, they have used their kgs dataset
> in a first try (which is in another part of the paper referred to
> being a 6d+ data set).
>
> Am 04.02.2016 um 18:11 schrieb Álvaro Begué:
> > The positions they used are not from high-quality games. They
> > actually include one last move that is completely random.
> >
> > Álvaro.
> >
> >
> > On Thursday, February 4, 2016, Detlef Schmicker <ds2 at physik.de>
> > wrote:
> >
> > Hi,
> >
> > I try to reproduce numbers from section 3: training the value
> > network
> >
> > On the test set of kgs games the MSE is 0.37. Is it correct, that
> > the results are represented as +1 and -1?
> >
> > This means, that in a typical board position you get a value of
> > 1-sqrt(0.37) = 0.4  --> this would correspond to a win rate of 70%
> > ?!
> >
> > Is it really true, that a typical kgs 6d+ position is judeged with
> > such a high win rate (even though it it is overfitted, so the test
> > set number is to bad!), or do I misinterpret the MSE calculation?!
> >
> > Any help would be great,
> >
> > Detlef
> >
> > Am 27.01.2016 um 19:46 schrieb Aja Huang:
> >>>> Hi all,
> >>>>
> >>>> We are very excited to announce that our Go program, AlphaGo,
> >>>> has beaten a professional player for the first time. AlphaGo
> >>>> beat the European champion Fan Hui by 5 games to 0. We hope
> >>>> you enjoy our paper, published in Nature today. The paper and
> >>>> all the games can be found here:
> >>>>
> >>>> http://www.deepmind.com/alpha-go.html
> >>>>
> >>>> AlphaGo will be competing in a match against Lee Sedol in
> >>>> Seoul, this March, to see whether we finally have a Go
> >>>> program that is stronger than any human!
> >>>>
> >>>> Aja
> >>>>
> >>>> PS I am very busy preparing AlphaGo for the match, so
> >>>> apologies in advance if I cannot respond to all questions
> >>>> about AlphaGo.
> >>>>
> >>>>
> >>>>
> >>>> _______________________________________________ Computer-go
> >>>> mailing list Computer-go at computer-go.org <javascript:;>
> >>>> http://computer-go.org/mailman/listinfo/computer-go
> >>>>
> >> _______________________________________________ Computer-go
> >> mailing list Computer-go at computer-go.org <javascript:;>
> >> http://computer-go.org/mailman/listinfo/computer-go
> >
> >
> >
> > _______________________________________________ Computer-go mailing
> > list Computer-go at computer-go.org
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> >
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