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Re: [computer-go] Modern brute force search
At 10:05 11-11-2004 -0500, Don Dailey wrote:
>
>Richard,
>
>Vincent is NOT saying that there is a player who knows the best line.
>He is saying that if a hypothetical computer was built that could
>calculate the best line, the top players would commit it to memory.
>
>Of course I think Vincent underestimates the difficulty of doing this.
>I doubt there is a single "best line", there must be many ways to play
>a perfect game of GO.
I am sure there is just 1 line.
in chess egtb's we can clearly see that the optimal play involves usually a
single line.
Only when it is real simple then there is sometimes more choices.
>Just as a silly example, let's say it turns out that Chess is a draw
>from the opening position. Both white and black players must learn
Please assume white begins and wins. At the top level a top GM tries to
draw with black and hopes for a win with white.
If white begins and wins things are more difficult in chess.
idemdito in go. black begins and wins. no question about it.
>every possible way to achieve this result. Let's say that it's a draw
>against all 20 of the first possible moves. The black player must
>learn the correct response to every one of these 20 moves because he
>doesn't know which white will choose. The white player could
>specialize in just one of those first moves. However it will probably
>be the case that black has more than one "drawing" response to
>whatever move white chooses. White will be forced to know how to
>respond to each of these. Each player can take turns "specializing"
>in one subtree at each point, but it's easy to see this will still
>quickly mushroom out of control.
A major problem for software, and this problem is not easy to solve, is
that the longest line from a human viewpoint is very trivial to see usual.
It's the medium term 'computerish tactics' that is hard.
>A really strong human would benefit enormously from this knowledge,
>perhaps the equivalent of several hundred ELO rating points, but it
>still wouldn't guarantee a draw because he simply could not remember
>the whole tree of possibilities. What a really great player could
You seem to underestimate what professional players, go or chess usually know.
Usually they know more books than even the biggest hand written openings
book of a chessprogram. And that's several million big.
>attempt to do is memorize enough of the tree to get him to positions
>he feels very comfortable with, but this wouldn't be fool-proof.
memorizing is very simple. most players never forget any game they played.
it would be wishful thinking that in go the things aren't the same.
>In GO, it's even more unlikely that even a top player could memorize
>enough sequences to play perfectly, and I even doubt it would bring
>the level of play up very much since it would probably be common
>practice to quickly get away from the most "obvious" continuations in
>order to nullify the memorization.
In Go from human viewpoint many sequences are near to forced. The play
happens at a very tiny area of the board. That's why reading deep in go is
not a single problem.
Even a real poor go player has no problems to calculate a deep forced win
there.
In such forced wins usually there is many moves which from computer
viewpoint are 'unforced' by any definition.
A human just knows: "this move is needed to garantuee X Y Z".
No computer knows that. Go or chess.
Just imagine a pro player.
A good example is perhaps 10x10 draughts. Right from the start software
found tactical tricks which no human could ever find. Any trick from a
world champion was found instantly.
Yet for example my friend Marcel Monteba who plays at a master level
strength (doesn't have a title yet), he easily can beat any software.
>From a mathematical viewpoint it is very difficult to explain to scientists
why chess is so much simpler.
>From human viewpoint it is very simple.
In chess, just centralize your pieces and you win.
In draughts the center is not so important like in chess.
So building up is very important.
It's very difficult to explain to a program why a certain move doesn't
build up the position.
Now imagine this, draughts is 10x10 board from which 50 squares get used.
Go has exactly the same symmetry like chess, but also the center initially
is not so important.
That means that the move selection from human viewpoint is very simple and
from a computer viewpoint real terrible.
So a perfect playing database when using opponent modeling (see v/d Herik
and others for this publication www.icga.org), it is very well possible
that the computer plays a move after which the very deep win is just very
logical for a professional player as he just sees 1 move at a time as the
rest sucks. Especially in Go this scenario is very likely.
So if professional players, who already will go up a lot in strength by
being able to research what perfect play looks like, if you put them
against a 361 stone database, then obviously it's real difficult to fool them.
Just don't underestimate how good human learning is.
So far human learning has always outclassed anything else in the universe.
>- Don
>
> Date: Thu, 11 Nov 2004 08:21:20 -0600
> From: Richard Brown <rbrown@xxxxxxxxxxxxxxxxx>
>
> Vincent Diepeveen wrote:
> > In whatever game we play.
> >
> > The 361 stone go database will beat of course every player very easily,
> > just like a 32 stone database in chess will beat the strongest
players very
> > easily.
> >
> > The reality is of course that by the time we have a 32 stone database
and
> > that there will be a 361 stone database for go, that players have looked
> > into it and already know the best line by head.
>
> Really? Do you know a go player who knows the "best line"? Wow!
>
> > So they can win with white in chess and with black in go very easily
when
> > using the optimum line.
>
> Well, sure, theoretically. That is to say, _if_ they know the optimum
line.
>
> Again, I must ask, who is this go player, who knows the optimum line?
>
> I think that the rest of the go world would like to meet this great
master!
>
> --
> Richard L. Brown Office of Information Services
> Senior Unix Sysadmin University of Wisconsin System
> 780 Regent St., Rm. 246
> rbrown@xxxxxxxxxxxxxxxxx Madison, WI 53715
>
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