I remember another way to estimate peak capabilities. This one was used in the
late 1970's by Ken Thompson / Belle, but maybe was invented earlier: play
handicap matches at different time controls, and fit a quadratic curve to the
data. If your program is strong enough, then additional
>So a small error in the opening or middle game can literally be worth anything
>by the time the game ends.
These are my estimates: human pros >= 24 points lost, and >= 5 game-losing
errors against other human pros.
I relayed my experience of a comparable experiment with chess, and how those
>
> On 15.03.2016 13:10, Petr Baudis wrote:
>
>>AlphaGo has won the final game, tenaciously catching up after a tesuji
>> mistake in the beginning
>>
>
> No. Do not trust Redmond's positional judgement. IMO, after the initial
> tesuji sequence, the position was balanced. (Kim said: White was a
Congratulations!
On 15.03.2016 13:10, Petr Baudis wrote:
AlphaGo has won the final game, tenaciously catching up after a tesuji
mistake in the beginning
No. Do not trust Redmond's positional judgement. IMO, after the initial
tesuji sequence, the position was balanced. (Kim said: White was
I would also like to congratulate the Alpha-Go team for this fantastic
result now when the dust have settled!
I think after all games have been played me feeling is that Alpha-go is
a little stronger then 9 Dan pro level, but of course still far away
from
perfect play.
My suspicion of the
AlphaGo has won the final game, tenaciously catching up after a tesuji
mistake in the beginning - a great data point that it can also deal with
somewhat disadvantageous position well. It has received honorary 9p
from the KBA.
I can only quote David Silver: "Wow, what an amazing week this has
