Quoting Dave Dyer <[email protected]>:
But you have never (to my knowledge) layed out what way that is.
You're quite right here. I'm not advocating a specific change,
just pointing out that all the effort going into building faster
monte carlo engines may be irrelevant, because the programs actually
need better steering.
I have been working on Valkyria since 2006. Everytime I do something
it becomes slower. Meanwhile it has become about 1000 Elo points
stronger (Only 200 Elo is due to faster computer). If you talk about
people on running their programs on as large clusters as possible,
then I may agree, but otherwise I think you misunderstand completely
what people are doing to improve their programs.
I know we disagree on this point, but I believe chess has reached
it's current state of success MOSTLY because of Moore's law.
It always was believed that Go was would have to be solved by other
means, perhaps even (gasp!) understanding the game. Monte carlo
has given some credibility to the theory that Moores law may be
enough after all. I'm arguing not.
Monte-carlo search *is* the "other means". Random exploration is
exactly what I do when I play go. The only difference is that my
search is goal directed so many playouts is just a 3-10 ply deep
locally. As consequence I am weaker than MC-program in actually
evaluating the whole board position. This weakness means I have to
painfully compensate for it by counting territory to set the ambition
for the goals I search. I sometime have a great intutions about
playing some vital point. This caused by nothing else but the human
variant of AMAF.
Sure I do have a rich set of concepts that pop up in my thinking. But
I am afraid that this are just labels that I attach to my search
results. I think higher level concepts are very important for
communicating about go, but they are irrelevant for actually playing
well.
The kind of knowledge about go that actally is essential for computers
and humans is the ability to play tactically correct quick and without
error. This means undrstanding L&D, seki, semeai, ladders and so on.
And this is also what makes Valkyria strong.
The reason Valkyria is not yet unbeatable is that the knowledge the
playouts have is still on a kyu level and very fragmented. There are
situations where I see the obious move in an instant where Valkyria
needs to search using several 100 playouts to get it right. In many
cases it plays perfect 100% of the time.
Get the fundmental knowledge right + MCTS = strong go
This has nothing to do with Moores Law. Valk3.5_100 is rated 1881 for
9x9 which is stronger than Gnugo. It only plays 100 playouts. When I
started doing MC evaluation with Viking5 in 2005 I had to spend 100000
playouts to get close to beating gnugo.
Just another perspective
Magnus
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