Hi all,
I've been looking through the archives trying to find out if anybody had
published information on the following during uniform random playouts
and/or real games:
- Frequency of string merges
- Frequency of placing stones in empty space
- Average length of strings, etc.
I noticed
Donn, your email at d...@mit.edu is bouncing.
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Hi Yamato,
Could you give us the source code which you used? Your algorithm is
too complicated, so it would be very helpful if possible.
Actually I think the source code would be much harder to understand!
It is written inside RLGO, and makes use of a substantial existing
framework that
David Silver wrote:
Hi Michael,
But one thing confuses me: You are using the value from Fuego's 10k
simulations as an approximation of the actual value of the position.
But isn't the actual
value of the position either a win or a loss? On such small boards,
can't you assume that Fuego is
Hi Remi,
What komi did you use for 5x5 and 6x6 ?
I used 7.5 komi for both board sizes.
I find it strange that you get only 70 Elo points from supervised
learning over uniform random. Don't you have any feature for atari
extension ? This one alone should improve strength immensely (extend
David Silver wrote:
A: Estimate value V* of every position in a training set, using deep
rollouts.
B: Repeat, for each position in the training set
1. Run M simulations, estimate value of position (call this V)
2. Run another N simulations, average the value of psi(s,a) over all
