On Thursday 07 August 2003 05:29, Darren Cook wrote:
I'd be really interested to see the results of such a
program. I believe gnugo can be set to output tactical
search results from an input position, so making the
training data may not actually be that hard.
NeuroGo uses tactical search result as an input, although it
reads only ladders (which 3 liberties allowed at the target
block until depth 2) and this is indeed an important input
feature.
As Nici pointed out, it slows down processing the position,
but reduces the number of games necessary for training.
Unforunately I cannot precalculate the input, since I found
learning from self-played games by far superior to learning
from master games.
Really? My sense from the literature was that most people had found
the opposite. We're running some experiments on this now, so we should
be able to add another data point to this question. I expect that the
best results will come from watching master games to get a rough idea
of what moves are good (e.g., don't play on the first line) and then
tuning with self-play.