[computer-go] Amsterdam 2007 paper

[Sylvain Gelly]

Hi Rémi,

Thank you for this paper. I found the work very interesting, well
written, and the paper is clear and pleasant to read.
As two things are modified in the same time (simulation policy and
tree search), I wonder what is the contribution of each part in the
overall improvement. For example I wonder what is the exact
improvement of the new policy simulation on itself (without modifying
UCT) over the one of MoGo. I guess you already have those results, but
don't have enough room to put it on this paper. For example, if I
remember correctly plain UCT with MoGo's simulation policy at 70k per
move was 83% against gnugo 3.6. What is the result with your
simulation policy? 85%/90%/95 %/ more?
That would help to know where this approach is more usefull:
simulation, tree or even both. I mean it is possible that combining
the two improvements makes a stronger player that taking the sum of
each improvement. If so, that would mean that some win-win effect
arises, and the tree search part type has to be related to the
simulation type.

Again, very interesting work.
Sylvain

2007/5/17, Rémi Coulom <Remi.Coulom at univ-lille3.fr>:
> Hi,
>
> I first thought I would keep my ideas secret until the Asmterdam
> tournament, but now that I have submitted my paper, I cannot wait to
> share it. So, here it is:
>
> http://remi.coulom.free.fr/Amsterdam2007/
>
> Comments and questions are very welcome.
>
> Rémi
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