
By sparring with AlphaGo, researchers are learning how an algorithm thinks - chwolfe
https://qz.com/897498/by-sparring-with-alphago-researchers-are-learning-how-an-algorithm-thinks/
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alanfalcon
So I've been following the english Go community as an outsider ever since the
first AlphaGo matches, and it's been great and fascinating to see what an
impact AlphaGo has had across all levels of play.

Fan Hui has the advantage of being able to peek behind the curtain, but other
pro players have still been studying every public AlphaGo match to try to find
what sequences and types of moves it prefers, and which well-known and
commonly accepted sequences it completely avoids. The problem, of course, is
that if you simply imitate without understanding then you may end up doing
stupid things. In fact, even AlphaGo did this against Lee Sedol whenever it
played out forcing moves which only served to limit its options and point
potential—in some cases strictly losing itself points—all because nobody
teaches AlphaGo that when humans play these moves it's often because they're
into overtime and simply have to play a move before time runs out to avoid
losing on time, and it gives the human more time to read out a complicated
sequence elsewhere on the board.

So while it's interesting and potentially helpful to be able to predict and
imitate an algorithm, AlphaGo helps show how it's even better to learn, as Fan
Hui is attempting to do, what's really going on behind the scenes.

Despite never having placed a Go stone in my life, I have particularly enjoyed
Nick Sibicky's Go lectures on YouTube. This one analyzing some of AlphaGo's
tendencies from its recent online matches is particularly interesting:
[https://youtu.be/v8Eh41m7gVA](https://youtu.be/v8Eh41m7gVA)

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nerdponx
This is a lot like constructing a partial dependence plot [1][2] for a very,
very sophisticated predictive model.

1: [http://scikit-
learn.org/stable/auto_examples/ensemble/plot_p...](http://scikit-
learn.org/stable/auto_examples/ensemble/plot_partial_dependence.html) 2:
[https://cran.r-project.org/web/packages/datarobot/vignettes/...](https://cran.r-project.org/web/packages/datarobot/vignettes/PartialDependence.html)

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gort
Link didn't work for me, but Google brings up this:

[https://qz.com/897498/by-sparring-with-alphago-
researchers-a...](https://qz.com/897498/by-sparring-with-alphago-researchers-
are-learning-how-an-algorithm-thinks/)

