No information is thrown away with maximizing win rate.
:-)
This is because in go it is only the sign of the final board count
that matter.
Yes I know I am very stubborn and narrow minded on this issue.
It is a weird thing to fear throwing away "information" and then
estimate the expected score which will throw away the actual
distributions of outcomes. And so will any other statistical measure do.
Also I do measure the score in at least two ways in Valkyria. One is
simply taking the average of score at the root and the other is to
estimate territory directly by looking at black/white membership of
individual points of the board. The latter is much more stable and the
average is often off several points also late in the endgame.
It could also be that different programs have very different kind of
playouts. I know that the playouts of Valkyria contains really weird
stuff. Sometimes black wins a playout with +100 points because a lot
of perfectly safe white groups died because of some really unlikely
combination of bugs, omissions and randomness in the playout. Such a
score does not give me information with any value.
I do agree that maybe expected score could be useful in the opening,
because the opening has no systematic bias yet. In the endgame however
almost every group will have a small probability of flipping state
from alive to dead or dead or alive, which has a little to do with
actually theoretical score of perfect play. But these probabilities
will add up to something that on average close to the true value but
mostly it will be very wrong.
So in short, I think win rates is the most robust thing to evaluate
positions using MC playouts. And someone else have to prove me wrong!
I wont do it. (But if someone do prove me wrong I will of course steal
the idea and implement it).
-Magnus
Quoting Łukasz Lew <[email protected]>:
On Tue, Oct 5, 2010 at 15:34, <[email protected]> wrote:
Quoting Łukasz Lew <[email protected]>:
Your dynamic komi results are very convincing..
But shouldn't we just concentrate on maximizing score instead of
winning rate in the beginning of the game?
Maximizing winning rate means that the probability of having a score > 0 at
the end of the game is maximum.
I want to maximize expected score of a playout.
I think that if we set komi so that around half of the playouts have
score > 0
AND if the noise is large (the game is in the beginning) then
maximixing winning rate
is almost the same as maximizing score.
The drawbacks of maximizing winning rate are:
- we need to adhoc adjust komi to tell engine to concentrate on
maximizing score
- we throw away information.
Of course maximizing winning rate is the right way in low-noise
conditions (endgame).
Exactly what do you mean with "maximizing score in the beginning of the
game"?
It is hard to estimate the score. Also in a game of go territory is not
everything. Aji and influence is also important. Win rate is as far as i
know the best way of capturing all these things in one measure that guides
search.
Magnus
_______________________________________________
Computer-go mailing list
[email protected]
http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
--
Łukasz
_______________________________________________
Computer-go mailing list
[email protected]
http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
_______________________________________________
Computer-go mailing list
[email protected]
http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
