[Computer-go] mcts and tactics

David Wu lightvector at gmail.com
Tue Dec 19 17:46:31 PST 2017


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 understood" by one side or the other and possibly even got
played out, it seems like the neural net would have a significant incentive
to learn them, step by step.

On Tue, Dec 19, 2017 at 7:57 PM, Andy <andy.olsen.tx at gmail.com> wrote:

> 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 network itself can read at least some
> simple whole board ladders, ladder breakers, and ladder makers. I would
> find it a large oversell if they just mean the MCTS search reads the ladder
> across the whole board.
>
>
>
> 2017-12-19 18:16 GMT-06:00 Stephan K <stephan.kunne at gmail.com>:
>
>> 2017-12-20 0:26 UTC+01:00, Dan <dshawul at gmail.com>:
>> > 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.
>>
>> Note that the input to the neural networks in the version that played
>> against Lee Sedol had a lot of handcrafted features, including
>> information about ladders. See "extended data table 2", page 11 of the
>> Nature article. You can imagine that as watching the go board through
>> goggles that put a flag on each intersection that would result in a
>> successful ladder capture, and another flag on each intersection that
>> would result in a successful ladder escape.
>>
>> (It also means that you only need to read one move ahead to see
>> whether a move is a successful ladder breaker or not.)
>>
>> Of course, your question still stands for the Zero versions.
>>
>> Here is the table :
>>
>> Feature                 # of planes             Description
>>
>> Stone colour            3                               Player stone /
>> opponent stone / empty
>> Ones                    1                               A constant plane
>> filled with 1
>> Turns since             8                               How many turns
>> since a move was played
>> Liberties                       8                               Number of
>> liberties (empty adjacent points)
>> Capture size            8                               How many opponent
>> stones would be captured
>> Self-atari size         8                               How many of own
>> stones would be captured
>> Liberties after move            8                       Number of
>> liberties after this move is played
>> Ladder capture  1                               Whether a move at this
>> point is a successful ladder capture
>> Ladder escape           1                               Whether a move at
>> this point is a successful ladder escape
>> Sensibleness            1                               Whether a move is
>> legal and does not fill its own eyes
>> Zeros                   1                               A constant plane
>> filled with 0
>>
>> Player color            1                               Whether current
>> player is black
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>
>
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