[Computer-go] Fwd: Teaching Deep Convolutional Neural Networks to Play Go
alvaro.begue at gmail.com
Mon Mar 16 02:07:09 PDT 2015
The human brain is not the most powerful AI, because it fails the "A" test.
I suspect bootstrapping is not very hard. I have recently written a Spanish
checkers program starting with no knowledge and I got it to play top-human
level checkers within a few weeks.
You can build a database of games as you go. The important thing is that
the games don't have to be played perfectly: They just need to be
significantly better than your current model, so you can tweak the model to
learn from them. In the case of checkers the "model" is the evaluation
function, for which I used a small neural network. In the case of go the
model could be an evaluation function or it could be something that assigns
probabilities to moves. In either case, a database with hundreds of
thousands of games played by the current version of the program is very
useful to refine the model. A few iterations of (1. build database using
current model, 2. train model using database) should figure out how to play
the game well without any human knowledge.
On Mon, Mar 16, 2015 at 4:52 AM, Darren Cook <darren at dcook.org> wrote:
> > To be honest, what I really want is for it to self-learn,...
> I wonder if even the world's most powerful AI (i.e. the human brain)
> could self-learn go to, say, strong dan level? I.e. Give a boy genius a
> go board, the rules, and two years, but don't give him any books, hints,
> or the chance to play against anyone who has had access to books/teaching.
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> Computer-go at computer-go.org
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