[computer-go] Congratulations to AyaMC, GNU, and MonteGNU!

[Don Dailey]

Joel Veness wrote:
> Hi Don,
>
> That is an interesting idea, and I don't see anything wrong with it in
> principle.
>
> However, given how slow Goanna is these days, I think I would probably
> gain more by spending 1/10 of the time needed for that idea on simple
> optimization! :)
>   

Yes, I don't use the idea myself,  I just do the simple test for 0.95.  
However sometimes doing the "more correct" thing actually is just as
simple.     I think this would be just a little piece of code that would
actually replace the conditional branching and perhaps even make the
code look cleaner.

If I ever get around to implementing it myself,  I'll let you know.

- Don


> Joel
>
> On Tue, Feb 5, 2008 at 2:44 AM, Don Dailey <drdailey at cox.net> wrote:
>   
>>  Joel Veness wrote:
>>  > Hi Nick,
>>  >
>>  > Goanna (agog) timed out annoyingly in that game against GNU.
>>  >
>>  > I have since implemented a rule: "if after some number of samples you
>>  > have a winning probability that is very close to 1.0, just make the
>>  > best move right away". There is no need to spend so long thinking in
>>  > these ridiculous endgame positions. I made some other changes so that
>>  > passing is more highly favored in certain situations, so hopefully
>>  > this will be the last time Goanna forfeits a game due to time.
>>  >
>>  My rule is that if the score if over 0.95  or under -0.95  I allocate
>>  some fraction of the time I normally would to that move.   I think my
>>  fraction is 1/10.    I always play the move with the most samples,  but
>>  for this I make sure than the highest scoring move (even with low
>>  samples)  fit's this window.
>>
>>  I think technically these kinds of algorithms should be applied
>>  gradually,  so some function could be applied to the score to determine
>>  how soon to stop.    The function should not be linear but should be
>>  such that very little reduction is applied unless the score is extremely
>>  high or low.      For instance is the score is 80% you might benefit
>>  from a slight reduction, but not much.
>>
>>  To find the right numbers, you would probably need to analyze a LOT of
>>  data and see how often you lose (and why) when the score is fairly
>>  high.   Probably not worth the effort!
>>
>>  This function should be fitted to your general time control algorithm
>>  too.   If you have rules to shorten the search,  you should definitely
>>  balance this by being more aggressive about time allocation earlier in
>>  the game.      It would  probably be very difficult to find a good
>>  balance but the right algorithms should cause you to lose some games and
>>  win some games but to win more than you lose.     If your are too
>>  conservative it might seem ok, but that causes you to lose games too,
>>  you just don't notice it as much.
>>
>>  - Don
>>
>>
>>
>>
>>
>>
>>
>>  > I guess that is what I get from only testing on CGOS. The small time
>>  > increment CGOS gives makes a big difference with the high latency I
>>  > get due to being based in Sydney, and to the best of my knowledge, KGS
>>  > doesn't do the same.
>>  >
>>  > Joel
>>  >
>>  > On Tue, Feb 5, 2008 at 1:32 AM, Nick Wedd <nick at maproom.co.uk> wrote:
>>  >
>>  >> Congratulations to the three winners of yesterday's KGS bot tournament
>>  >>  (there was a tie in the Formal division, so three winners).  My report
>>  >>  is at http://www.weddslist.com/kgs/past/35/index.html
>>  >>
>>  >>  Nick
>>  >>  --
>>  >>  Nick Wedd    nick at maproom.co.uk
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>>  >>
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