There are two distinct concepts here.  There is precision and there is
accuracy.  Your test will test precision (how exact the estimate is), but it
fails to test accuracy (a measure of how close the mean is to the actual
value).  But, I do think that knowing the precision is useful.  If the
precision is too high (the noise is too low), it indicated that too many
simulations (on a given position) were done for efficient use of processing
power.  Atleast that is my perception of the situation.

   In a more general sense, I think that data gathering is definately by
far one of the most useful ways to contribute to the computer go community
and I salute you for your proposal.

- Nick

On 6/16/07, Heikki Levanto <[EMAIL PROTECTED]> wrote:

It seems generally accepted that MC or UCT programs are weakest in the
opening. My own experience matches this too. Some times I get the idea
that my program doesn't know at all what it is doing the first few
moves. I propose a simple test to see if that is the case. Before doing
it, I'd like to hear if other programmers are willing to make a similar
test, and agree on the particulars.

The idea is simple: We know that the empty board is symmetrical. How
many iterations does it take before the program gets values for the
first move that are symmetrical too. For example, if the program prefers
the 3-3 point in one corner, but 4-4 in the other corner, then I would
say that it doesn't know much about the situation.

I am sure there is a mathematically sound way to measure how symmetric
the evaluation is, but my math is a bit rusty, so I am asking if someone
can come up with a good way. After that, I'm asking if various
programmers would be willing to run this test, and publish the results?

- Heikki
  (who has no time to debug his own program...)


--
Heikki Levanto   "In Murphy We Turst"     heikki (at) lsd (dot) dk

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