Hello.
I updated my master thesis (http://ark.qp.land.to/main.pdf). This is a final
version.
I added a experiment, and I increased the number of matches with GNUGo to 600.
It makes the conclusion more certain.
My English does not be corrected, sorry. I will practice writing English.
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Hello, Remi Coulom.
>Also, even worse than that, for a given set of features, the pattern
>urgencies computed by MM are not optimal. That is to say, it is possible
>to manually tweak urgencies and get a stronger program.
I have considered this, and I think that this may be caused by wrong
trai
Hello.
Hi,
>I would like to confirm your experiments: I have noticed already that
>adding shapes of radius > 4 improves prediction a lot, but does not
>improve playing strength (from progressive widening).
I have not yet tuned progressive widening. This information is helpful for my
experiment
Hello.
>Hi,
>Sorry for announcing too early. Your English is maybe a bit exotic, but
not too difficult to understand. I appreciate your effort to write in English.
In the computer science course that I belong to, we have to write
master thesis in English (even graduation thesis).
>Also, I b
Hello, Coulom. I'm Nobuo Araki.
Thank you for reading my thesis. However, this thesis is first version, not
final version. Therefore, there are too few experiments. And Mr. Hideki Kato
sent me many warnings about this thesis, for example "English is too bad." You
may be confused while reading m
Thank you for responding to my question, everyone.
>Nijhuis
Great! Thank you for your advice.
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Hello. I'm Araki. Nice to meet you.
I'm searching researches about human annotation to game records for machine
learning. (for example, "these stones are weak", "this move is for attack those
stones", "this move was bad" ...etc) Does anyone know such researches?
