Hi Daniel,
AGZ paper: greedy player based on policy network (= zero look-ahead) has an
estimated ELO of 3000 ~ Fan Hui 2p.
Professional player level with Zero look-ahead. For me, it is the other
striking aspect of 'Zero' ! ;-)
IMO, this implies that the NN has indeed captured lots of tactics. Eve
>I wouldn't find it so surprising if eventually the 20 or 40 block networks
>develop a set of convolutional channels that traces possible ladders
>diagonally across the board.
Learning the deep tactics is more-or-less guaranteed because of the interaction
between search and evaluation throug
I wouldn't find it so surprising if eventually the 20 or 40 block networks
develop a set of convolutional channels that traces possible ladders
diagonally across the board. If it had enough examples of ladders of
different lengths, including selfplay games where game-critical ladders
"failed to be
How do you interpret this quote from the AGZ paper?
"Surprisingly, shicho (“ladder” capture sequences that may span the whole
board) – one of the first elements of Go knowledge learned by humans – were
only understood by AlphaGo Zero much later in training."
To me "understood" means the neural net
You guys are killing me.
Let's do what the space science guys did;
Parallelize via slow computation. If you need me to handle errors, I can do
ecc's. I know about how to correct for errors.
Why are we all trying to find compute power independently? Let's just add
it up. There's no real money her
2017-12-20 0:26 UTC+01:00, Dan :
> Hello all,
>
> It is known that MCTS's week point is tactics. How is AlphaZero able to
> resolve Go tactics such as ladders efficiently? If I recall correctly many
> people were asking the same question during the Lee Sedo match -- and it
> seemed it didn't have a
Hello all,
It is known that MCTS's week point is tactics. How is AlphaZero able to
resolve Go tactics such as ladders efficiently? If I recall correctly many
people were asking the same question during the Lee Sedo match -- and it
seemed it didn't have any problem with ladders and such.
In chess
There is not much to achieve there though.
It is expected that an AI will be able to outplay a Human opponent simply
on micro tricks. Perfect single unit micromanagment across the entire map
can easily gain a large enough edge, that the strategic decision making
with imperfect information doesn't
>I was thinking about this development and what it may mean from the point
of view of a more general AI.
>I daresay the next experiment would be to have just one neural net playing
the >three games, right?
>To my understanding we still have three instances of the same *methodology* but
not yet a si
Google has already announced their next step -- Starcraft2. But so far the
results they published aren't mind blowing like these.
2017-12-19 9:15 GMT-06:00 Fidel Santiago :
> Hello,
>
> I was thinking about this development and what it may mean from the point
> of view of a more general AI. I da
Hello,
I was thinking about this development and what it may mean from the point
of view of a more general AI. I daresay the next experiment would be to
have just one neural net playing the three games, right? To my
understanding we still have three instances of the same *methodology* but
not yet
Hi,
The Computer Olympiad was announced yesterday:
"
Dear Colleagues,
The ICGA is pleased to announce that the 2018 Computer Olympiad and the 10th
International Conference on Computer and Games (CG 2018) will be held in
Taiwan, from July 9th-13th inclusive.
The Chess events, including the Wor
12 matches
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