Hi Hendrik,
Thanks.
Congratulations, you have done a really nice work. I check your thesis. My
result is consistent with yours of LBR-2. No benefit at all, so I took it
off. I adapt LGR-1 to softmax policy of Erica. Basically, I am tuning the
probability offset by checking some aritifical test-positions. In 3000
playouts, now it scores around 57% after 500 games, almost 60%, which is my
target (my intuition is LGR-1 should help a lot already). :)
Actually I have one question and still can't figure out your reasoning. In a
playout, why do you over-write the earlier replies by the later ones? Using
the earliest one looks more reasonable to me.
Aja
----- Original Message -----
From: "Hendrik Baier" <>
To: <[email protected]>
Sent: Wednesday, January 26, 2011 5:00 PM
Subject: Re: [Computer-go] Computer-go Digest, Vol 12, Issue 79
Hi Aja,
I would be interested in your results. I think the LGRF policy is only a
small first step into the direction of more adaptive playouts (and
hopefully the overcoming of the horizon effect).
As for the Last-Bad-Reply idea, you can read about my experiences with
this and related policies in my Master's thesis, if you're interested. It
contains the idea that resulted in the "Power of Forgetting" paper as
well.
http://www.ke.tu-darmstadt.de/lehre/arbeiten/master/2010/Baier_Hendrik.pdf
regards,
Hendrik
I admit that it's difficult for me to include such deterministic default
policy. :-)
With softmax policy, using the information of "last-LOST-reply" is maybe
a good direction.
Aja
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