I disagree. If the opponent's estimate of the rest of the board is at least as
good as program XXX, but the opponent knows a particular group is 100% dead,
where program XXX thinks it might live, the opponent is likely to win, with a
probability approaching 1.00. Program XXX will be basing its decisions on
provably false information. The opponent will spend just enough effort to keep
that group dead, and will otherwise play as well as program XXX on the rest of
the board.
We have all seen that Mogo is not greedy - it will play suboptimal moves while
it thinks it has the win. I've read many an argument about how Mogo is actually
maximizing win probability; this is total fantasy. When obvious yose ( endgame
) plays or life-making plays are passed up in favor of tossing random stones
into perfectly secure eyespace, that is a losing strategy. Better yose
handling can ( and often does ) make up for earlier mistakes. Random stones in
one's own area will not help. Under area counting rules, playing the da me (
neutral points ) would be better.
Terry McIntyre <[EMAIL PROTECTED]>
“Wherever is found what is called a paternal government, there is found state
education. It has been discovered that the best way to insure implicit
obedience is to commence tyranny in the nursery.”
Benjamin Disraeli, Speech in the House of Commons [June 15, 1874]
----- Original Message ----
From: ivan dubois <[EMAIL PROTECTED]>
To: computer-go <computer-go@computer-go.org>
Sent: Wednesday, January 23, 2008 7:51:52 AM
Subject: Re : [computer-go] Bent four in the corner was:Scalability problem of
play-out policies
Hello,
I agree that the current implementation of Mogo (from what I know about it)
will not know for sure that the D17 black group is 100% dead.
It will think that it is X% dead and stick to that estimation, whatever
thinking time you give it. X is a constant that does not depend of thinking
time (no scalability).
However, and this can be surprising, I am not sure wether it is really a
scalability killer for whole board play, because after all, it doesnt have to
know with 100 % confidence the status of one group to play perfectly.
----- Message d'origine ----
De : terry mcintyre <[EMAIL PROTECTED]>
À : computer-go <computer-go@computer-go.org>
Envoyé le : Mercredi, 23 Janvier 2008, 16h24mn 53s
Objet : Re: Re : [computer-go] Bent four in the corner was:Scalability problem
of play-out policies
Feed any MC-UCT program the position after White B1, at move 195, and ask the
probability of a black win. Repeat until the program corrects its estimate.
It would be interesting to determine just how many simulations are needed to
solve this problem - which is obvious to double-digit kyu players.
Terry McIntyre <[EMAIL PROTECTED]>
----- Original Message ----
From: ivan dubois <[EMAIL PROTECTED]>
To: computer-go <computer-go@computer-go.org>
Sent: Wednesday, January 23, 2008 7:17:17 AM
Subject: Re : [computer-go] Bent four in the corner was:Scalability problem of
play-out policies
Hello,
After thinking a bit more about it, I came to the conclusion that the so called
"Bent four in the corner" shape, is not such a serious scalability killer (I
like this term).
Nor is the situation that appears in your game.
Let me explain why :
It would indeed be a scalability killer if Mogo was 100 % sure that some
group is dead, when it is actually alive. However what happens is that it has
some doubts about the situation. It may think for example it is 60 % alive and
40 % dead. Of course it would be better for him to know the reality, but having
some
persistent doubt on it is not that much detrimental. For example if he has
perfect information about the rest of the board, he will play perfectly on the
rest of the board.
I propose a chalenge to this list : Find a real scalability issue with Mogo or
any other actual UCT program. (And prove it)
Ivan
----- Message d'origine ----
De : Harald Korneliussen <[EMAIL PROTECTED]>
À : computer-go@computer-go.org
Envoyé le : Mercredi, 23 Janvier 2008, 15h31mn 20s
Objet : [computer-go] Bent four in the corner was:Scalability problem of
play-out policies
Ivan Dubois mentioned the bent four in the corner shape as a
scalability killer, a situation where more playouts
doesn't help
(much), because playouts systematically misevaluate it. As I
understand it, it could be corrected in the tree, but this is very
unlikely to happen until the very end of a game, by which time it may
be too late (Mogo having worked the entire game for that solid 0.5
win, which turns out to be a solid loss instead because of the
life-and-death misevaluation)
I recalled a KGS game of Mogo I'd looked at, where something very
similar happened, and with a little digging I found it again:
http://files.gokgs.com/games/2007/12/1/Ardalan-MoGoBot3.sgf
It turns out it's not the "bent four" shape, but I suspect it's
another such shape, where more playouts only confirm that "these moves
aren't worth including into the tree", so that UCT catches them very
late, if ever.
If these situations can be
reliably created by a human, then indeed
they put an upper limit on the "real world" scalability of a program.
If I should propose a hackish heuristic to deal with such situations,
this is it: At one point, when the problematic shape appeared, the
human must have done a move that to the computer seemed horribly bad.
"Why did he do that? Doesn't he see that my shape is alive?". When
such situations occur, there are two possibilities:
1. The bot is playing a weaker human player, and the move is indeed bad.
2. The bot is playing a stronger human, and the move is actually good.
I think it may be a good idea to do something with the weighting in
these situations, so that the relevant moves are added to the tree. In
worst case, a lot of effort is wasted in proving a bad move bad - but
this should not be so serious, as the bad move will likely mean the
opponent has poor chances of winning anyway. In the best
case, the
program's blunder is revealed after the fact. This may still leave
little chance of winning, (if the l&d error was severe) but at least
the program's counting won't be off for the rest of the game. Since
today's programs don't care for winning margins, counting errors by
even a single point will spell disaster.
I believe this heurtistic would be cheap in terms of computational
cost, but hard to evaluate/tune. Self-play would not be very
effective...
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