[computer-go] thoughts on 100,000 cgos games

[Don Dailey]

The statistics on CGOS appear to indicate that komi of 7.5 is
favors white by a small margin.   But probably 7.5 is as close
as we can get.  

When I sampled the games of a few prominent players (players who 
are quite active) individually, I could not see a clear trend.  
The games of the strong players did not show a significantly 
different color bias over any other players.

Here are the stat's:

ALL PLAYERS - Total games played  101035
  WHITE:   53924 = 53.37%
  BLACK:   57111 = 46.63%


Viking5 (1809)  played  3856
  WHITE:  2017 = 52.31%
  BLACK:  1839 = 47.69%


NeuroGo (1752)   played  4486
  WHITE: 2329 = 51.92%
  BLACK: 2157 = 48.08%


Anchorman (1500) played  15009
  WHITE:    7672  = 51.12%
  BLACK:    7337  = 48.88%  


ReadyToGo (1300) played   14175
  WHITE:   7484 = 52.80%
  BLACK:   6691 = 47.20%


IdiotBot (343) played  4439
  WHITE: 2290 = 51.59%
  BLACK: 2149 = 48.41%


On Mon, 2006-05-01 at 22:35 -0400, Don Dailey wrote:
> The "correct" komi probably can't be determined from these games 
> because many of the good programs play to win the game, not territory.
> 
> However, we can probably determine if the komi is too high or
> too low.
> 
> I have all the data in a sql database, when I get time I'll
> do a win/loss for all the programs that have played a significant
> number of games.
> 
> - Don
> 
> 
> 
> On Mon, 2006-05-01 at 17:33 -0700, David G Doshay wrote:
> > Reaching 100,000 games seems like a good milestone for reflection, so  
> > I hope that others will share their thoughts.
> > 
> > Of course, it is a great thing that Don has done to provide this  
> > service, and I thank him for his initiative and efforts.
> > 
> > I have more of a list of random observations than coherent opinions:
> > 
> > 1) It looks like most any of the programs can have their rating swing  
> > by 100 or more points, and it looks like it is the distribution of  
> > other programs on-line at the time that is causing at lease half of  
> > these swings. It looks like it is programs that are involved in  
> > clearly non-transitive relationships with other closely rated  
> > programs that this effects the most.
> > 
> > 2) With AnchorMan fixed at 1500, perhaps we should similarly fix  
> > Random at zero. It has shown that it tends to less than zero. I think  
> > this will really only change the scores of the programs that are not  
> > too much stronger than Random. While this really does not matter, it  
> > looks funny to have a program with a negative rating.
> > 
> > 3) While I had hoped that we might be able to do some machine  
> > learning on SlugGo's parameters by having quick access to so many  
> > opponents on this server, I have decided that without knowing who the  
> > opponent is, any learning done in this context would not be  
> > meaningful ... winning a game against any of the lowest ranked  
> > programs does not mean that SlugGo's moves were any good and thus  
> > gathering statistics about the success of moves in such a widely  
> > varied field of opponents might be a big mistake. This is leading us  
> > to some interesting discussions about machine learning, but we have  
> > no deep conclusions yet.
> > 
> > 4) It seems to me that there should now be enough data to determine  
> > if the komi being used is
> > the best one. My expectation is that the "best" komi will end up  
> > being different for different pairings, but hopefully something clear  
> > will come out of the analysis.
> > 
> > I would hope that this discussion does not just turn into a cgos wish- 
> > list, but if it does then please change the subject line.
> > 
> > Cheers,
> > David
> > 
> > 
> > 
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> 
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