| format | 7-round Swiss | |
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| board size | 19×19 | |
| rules | Chinese | |
| komi | 7½ | |
| time | 29 minutes plus 10/30s |
The first round started at 16:00 UTC.
Excluding forfeited games, Black won 11 games, White won 17 games, and there were 0 jigoes. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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In the table above, 0 is a loss 1 is a win J is jigo left superscript is the player's colour right superscript is the round in which the game was played a subscript shows how the result was determined: R for resignation T for time F for forfeit a number for the points difference after counting. All the 0s, 1s and Js are links to the game record. Black won 19 games and White won 17. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Seven players registered for the tournament. I therefore added GNU Go, running on a single processor of my own desktop PC. I believe that having this play is better than having byes. I believed that GNU Go was so weak that it would be unlikely to affect the result, but strong enough that it can win the occasional game. However, see below.
I have nothing to say about the actual play, as most of the players are stronger than me.
In round 4, gnugo3pt8 (rated at 6-kyu on KGS) beat nomiBot (rated at 2-dan). This surprised me. The game seemed unremarkable.
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| gnugo3pt8 vs NiceGo19N |
| After move 209 |
In round 6, gnugo3pt8 beat NiceGo19N (rated at 1-kyu). This surprised me more.
Again the game seemed unremarkable, with gnugo3pt8 making some poor moves, as I would
expect from a 6-kyu player. NiceGo19N's operator admitted that it sometimes loses to
version 3.9 of GNU Go when he is testing it.
I wonder if the reason that nomiBot and NiceGo19N lost to a much weaker player, is that
they are "trained" mostly against other Monte-Carlo bots, and have little experience of
playing against old-style bots like GNU Go. But as the ratings of all three are derived
from their games against human opponents, this is not a convincing explanation.
Oakfoam (playing as NiceGo19N)'s programmer Detlef Schmicker has responded
It was one of the observers who tested oakfoam against gnugo 3.9, not me. Our actual download version is missing the large pattern database, so it is not comparable I think.
We read the top left in the game not dead enough (90% dead). as it is a big area this lead to significant miscount. As we do not have dynamic komi oakfoam gave away a lot of points, as it had 80% winrate for most of the middle game.
I think the probability of such problems is not so dependent on the opponent strength. If playing against even strong humans this happens from time to time and loosing does not harm the rating too much I think.
By the way, I am training mainly against gnugo level 0 and gnugo level 10. But never with mc enabled.
The diagram to the right shows position after Black played tenuki from the fight in the top left corner. It appears to me that the black group in the top left has no way to make a second eye, and that the game is very close.
Players receive points for the 2013 Annual KGS Bot Championship as follows:
| Zen | 8 |
| Aya | 4 |
| Many Faces of Go | 4 |
| GNU Go | 1 |
| Gomorra | 1 |
| nomitan | 1 |