3 ms·
My understanding is the weakness comes from the fact that convolutional nn are used and how the information propagates through layers. It's been known from the
by kuboble 4y ago
My understanding is the weakness comes from the fact that convolutional nn are used and how the information propagates through layers.
It's been known from the beginning that this kind of position (large cyclic hroups) is a weak spot of all bots based on those cnn.
What was not clear at all was whether it's possible to force those positions.
- espadrine 4y agoDefinitely true! Despite that, it is probably possible to make it detect this pattern, but only if it appears during training. The thing is that this becomes a vicious circle: the network fails to learn this because its architecture is not conducive to that, so it doesn't play it right with the limited self-play visit count, so the right line doesn't appear in the self-play, so it fails to learn it. KataGo adds a few situations in training which didn't appear in self-play, "blind spots" that a shallow search depth fails to notice as good moves, so that it still tries to learn from positions it would not generate. It is a little bit like learning to tie your shoelaces. Brains are not great at guessing the qualities of knots among all possible ties, but if you see it done once, you're set for life.