[Edu-sig] off-topic: apropos Go

[Mark Engelberg]

On Sat, Feb 12, 2011 at 1:46 AM, Christian Mascher <christian.mascher at gmx.de
> wrote:

>
>
> Interestingly the breakthrough achievement leading to todays much stronger
> programmes (only a couple of years back) did not come by mimicking human
> reasoning about the next move. Instead, the merit of a move is evaluated by
> a monte-carlo approach: The board is filled with random moves until the
> machine can tell who wins. This is repeated thousands of times and so by
> sheer statistics  the relative value of the next move is assessed. This kind
> of evaluation process is absolutely not what a human player is doing or
> capable of doing in his head. So there is no hope of computers teaching us
> how to play better Go ;-), at least not in the sense of explaining to us why
> they made a certain move.
>
>
My understanding is that the strongest Go programs use the Monte Carlo
method, evaluating the various moves against vast databases of past
professional games.  So they are not really mimicking human reasoning, but
are "data mining" the wisdom of humans.  The programs can report back some
info about why they made a certain move, usually in the form of "this move
was made in 60% of pro games in a similar position that eventually led to a
win".

In this sense, Go is proving to be a good example of the "new approach" to
AI.  For example, translation between foreign languages has undergone a
similar revolution.  20 years ago, it was all about building expert systems
with thousands of carefully crafted rules that capture the domain
knowledge.  These days, we just throw a large body of examples of
human-translated documents at a data mining program, and let it work out new
translations using statistical methods.
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