[computer-go] ego110_allfirst on CGOS

[Don Dailey]

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The version source I am looking at, does all-as-first and considers 7/8
of the moves.

The exact code for maximum move number to consider is:

  max = p->ctm + 2 + ( ecount - (ecount >> 3) );

where max is maximum move number (or ply of game) and
ecount is the number of moves executed in the play-out.
p->ctm is the current move number in the game that we are
doing the play-out for.

Then I tally up the stats for each move by the computer but only
if the computer was the first to play the move.

You should experiment a little to get the best settings but this
depends somewhat on the level.   For 1000 sims 7/8 is probably
better than the 5/8 I told you previously, which was apparently
the wrong number or I have the wrong source code.

- - Don





Jason House wrote:
> 
> 
> On 9/24/07, *Don Dailey* <drdailey at cox.net <mailto:drdailey at cox.net>> wrote:
> 
>     My impression is that you over-engineer (or over-think) everything.  You
>     try to improve on something before you've implemented something that is
>     simple and you know works reasonably well.
> 
> 
> My latest timing implementation is available under GPLv3 at [1].  It
> probably has a few warts still (including hard coded default values),
> but does seem to work relatively well.  It estimates mean and variance
> of the different sources of timing losses and then creates a confidence
> interval for how long the time losses for the remainder of the game will
> take.  The equation for this (for n future moves) takes the form
> a*n+b*sqrt(n).  It then treats time beyond that as spare time to
> allocate over moves.  While that final piece is simplistic (10% beyond a
> fixed min think time per move), I assume someone may find the
> statistical estimation stuff useful. 
> 
> External lag (AKA network lag) is relatively noisy because of time
> rounding issues.  To overcome this, I do not compute sample variance,
> but just the average delay observed in the game.  Variance is assumed to
> be a function of mean like in the exponential distribution.  Because of
> initial noise, the estimated mean slowly changes from a default value to
> the observed value.
> 
> Internal lag is assumed to have finer detail and both sample mean and
> variance are used after just a few samples.
> 
> [1]
> http://housebot.svn.sourceforge.net/viewvc/housebot/trunk/housebot/timecontrol.d?view=markup
> 
> 
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