Life In 19x19

Thanks lightvector. Pardon my ignorance but I'm using Lizzie 0.7 and Katago 1.2

I think the matter has been settled conclusively by yourself, others and the AI (recent versions with sufficient playouts).

I'll focus on the full endgame analysis now, using the knowledge provided here about the (ko) variations.

jlt wrote:KataGo does not only take into account winning percentages but also the number of points. KataGo may not play perfect endgame, but may be superhuman (i.e. makes fewer errors than humans)?

Oh, I think there is no question that KataGo and LZ play at a superhuman level. But not in every position.

I was reminded if this in a chess endgame lecture by Yasser Seirawan. ( https://www.youtube.com/watch?v=YI5CQL_ ... 3&frags=wn ) Chess engines have played at superhuman levels for many years. Seirawan showed a position that he had been sure at first sight was a win for Black. His engine, however, evaluated the position as only slightly favorable for Black. In his lecture, to illustrate Black's advantage Seirawan played as Black against the engine as White. After not many moves the engine reevaluated the position as equivalent to Black being a queen ahead or so. I got the impression that Seirawan enjoyed being better at the endgame than the engine.

Skill at both chess and go is multidimensional. In both games humans are still better in some ways than the programs.

Bill Spight wrote:But not in every position.

Of course I agree that some positions are more adapted to the human mind than to the engine. I just believe that KataGo makes fewer errors on average, even during the endgame phase.

In the variation showed by lightvector

Click Here To Show Diagram Code

[go]$$Wc
$$ ---------------------------------------
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . . . X X O X . . O . . . . O O . |
$$ | X X X X . X O X X . O . O O O O X X . |
$$ | X O O O X X O O O , . O X X X X 5 . 3 |
$$ | X X O O O O X . O X . O X . . 2 1 O . |
$$ | O O X O . . X . O O X X X . O 4 X X . |
$$ | . . . . . . . . . . O O O X O O O X . |
$$ | . O O O . . . O . . . X O O O X X . . |
$$ | . X O X O . . O . . . X X O X O X . . |
$$ | . O . X O . O X X , O X O X X , X . . |
$$ | . X X X . O X . . . . X . . . . X O . |[/go]

Black loses two stones but gets sente. Black could have saved them in gote by playing at . I wonder how a human reasoning could have come to the same conclusion that it's better to sacrifice the stones for sente.

jlt wrote:

Bill Spight wrote:I just believe that KataGo makes fewer errors on average, even during the endgame phase.

Endgame phase: do you think so even when KataGo is clearly ahead?

RobertJasiek wrote:

jlt wrote:I just believe that KataGo makes fewer errors on average, even during the endgame phase.

Endgame phase: do you think so even when KataGo is clearly ahead?

Unlike other bots, KataGo doesn't play stupid moves when it is clearly ahead, and I haven't heard of stronger players complaining about such behavior, so my initial guess is "yes"... But you are an endgame expert, so maybe you could try by yourself to feed KataGo a few endgame positions and check if it makes mistakes?

jlt wrote:

Bill Spight wrote:But not in every position.

Of course I agree that some positions are more adapted to the human mind than to the engine. I just believe that KataGo makes fewer errors on average, even during the endgame phase.

In the variation showed by lightvector

$$Wc
$$ ---------------------------------------
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . . . X X O X . . O . . . . O O . |
$$ | X X X X . X O X X . O . O O O O X X . |
$$ | X O O O X X O O O , . O X X X X 5 . 3 |
$$ | X X O O O O X . O X . O X . . 2 1 O . |
$$ | O O X O . . X . O O X X X . O 4 X X . |
$$ | . . . . . . . . . . O O O X O O O X . |
$$ | . O O O . . . O . . . X O O O X X . . |
$$ | . X O X O . . O . . . X X O X O X . . |
$$ | . O . X O . O X X , O X O X X , X . . |
$$ | . X X X . O X . . . . X . . . . X O . |

Click Here To Show Diagram Code

[go]$$Wc
$$ ---------------------------------------
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . . . X X O X . . O . . . . O O . |
$$ | X X X X . X O X X . O . O O O O X X . |
$$ | X O O O X X O O O , . O X X X X 5 . 3 |
$$ | X X O O O O X . O X . O X . . 2 1 O . |
$$ | O O X O . . X . O O X X X . O 4 X X . |
$$ | . . . . . . . . . . O O O X O O O X . |
$$ | . O O O . . . O . . . X O O O X X . . |
$$ | . X O X O . . O . . . X X O X O X . . |
$$ | . O . X O . O X X , O X O X X , X . . |
$$ | . X X X . O X . . . . X . . . . X O . |[/go]

Black loses two stones but gets sente. Black could have saved them in gote by playing at . I wonder how a human reasoning could have come to the same conclusion that it's better to sacrifice the stones for sente.

That's a question of evaluation. Humans are not bad at it in the endgame. Two stones for sente? Not much of a sacrifice. The key is to avoid the ko. And at first glance the ko looks good for White.

jlt, I need gaming hardware and time for such interesting studies. My office PC won't do.