[Computer-go] Alphago and solving Go

Erik van der Werf erikvanderwerf at gmail.com
Mon Aug 7 06:08:14 PDT 2017

On Mon, Aug 7, 2017 at 12:52 PM, Darren Cook <darren at dcook.org> wrote:

> > https://en.wikipedia.org/wiki/Brute-force_search explains it as
> > "systematically enumerating all possible candidates for the
> > solution".
> >
> > There is nothing systematic about the pseudo random variation
> > selection in MCTS;
> More semantics, but as it is pseudo-random, isn't that systematic? It
> only looks like it is jumping around because we are looking at it from
> the wrong angle.
> (Systematic pseudo-random generation gets very hard over a cluster, of
> course...)
The selection should be quite deterministic. Randomness is in the playouts,
so it only comes in indirectly. With a value net there will be even less

> > it may not even have sufficient entropy to guarantee full
> > enumeration...
> That is the most interesting idea in this thread. Is there any way to
> prove it one way or the other? I'm looking at you here, John - sounds
> right up your street :-)

Full enumeration may occur with infinite time & memory, and a growing
exploration term for unexplored nodes. Randomness has little to do with it.

Anyway, IMO the whole argument is silly and even a bit disrespectful. I
don't consider AlphaGo a brute force solution. However, if some
hard-pruning would turn AlphaGo from brute force into non-brute force then
just implement some provably correct hard pruning rules and you're done
(e.g., don't play in unconditional territory, stop the playouts when the
position is statically solved, etc.). I have things like that in
Steenvreter, but it doesn't feel like that changes the nature of the beast.

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