If scoring matters, then instead of just estimating the winrate for a certain 
move, a bot has to estimate a komi/winrate function.
As a shortcut, maybe a simoid scoring function will suddenly start to shine.
But that really folds winrate and winning score into a single dimension.
If that is too much of a simplification only testing can tell.
For humans it just means don't resign, don't try anything too funny to catch 
up, and don't take it too easy in a winning position.
Put even more shortly it means "don't bother counting" for humans, which is 
ironic because for bots it means exactly the opposite.

Stefan

  ----- Original Message ----- 
  From: Don Dailey 
  To: computer-go 
  Sent: Monday, November 23, 2009 1:22 AM
  Subject: Re: [computer-go] Hahn system tournament and MC bots


  I'm pretty sure that this simplification of the rules would favor computers.  
 Of course that would require some program modifications, primarily counting 
points on the board instead of wins and losses.

  These rules basically takes out some (or at least reduces) elements of the 
game that humans are better at, such as knowing how to judge risk, knowing when 
to go for it, etc.       Go is still way too complex for computers to process 
well so any simplification like this is going to help computers.  

  - Don




  On Sun, Nov 22, 2009 at 6:23 PM, Alain Baeckeroot 
<[email protected]> wrote:


    A Go tounrmaent with Hahn system has been retransmeted on kgs/eurogo TV
    With these rules, the actual count makes a difference (as opposed to just 
win/lose)

     Winning by >40.5        gets 100 points
     ...                                                    ...
     Losing by  >40.5        gets   0 point

    see  http://senseis.xmp.net/?Bangneki
    http://www.suomigo.net/wiki/HahnSystem

    How current MCx bots can handle this kind of rules ?

    The traditional safe way would ensure 60 points,
    but trying crazy things (when losing) would cost a lot
    if the result ends by losing by resignation or -40.5

    What is the impact for chosing the best move ?
    (choose the greediest amongst several with highest winning rate ?)

    Alain.
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