AlphaZero - Tactactical Abilities
Posted: Sat Dec 16, 2017 11:58 am
First, let me get this out of the way:
Of course it is impressive and interesting whenever a chess engine beats (a version of) Stockfish 28/72/0, whenever a newer approach shows promise against and older approach, whenever a new engine comes up with novelties or a different style of play than most other engines and so on.
On the other hand, I think it is too early to conclude anything definite for a lot of reasons that have already been discussed: It is impossible at the moment for scientific peers to reproduce the results, it is impossible for peers to experiment with the engines in other ways, far from all games have been published, Stockfish had multiple handicaps such as hardware (I know it is hard to make a direct comparison between the hardware platforms, but AlphaZero relies heavily on specialized hardware at the moment and the combined (hardware/software) approach of AlphaZero is not as interesting as an approach that can readily be used on regular hardware, from smartphones to powerful PCs like competing approaches), older version, tiny hashtable, fixed time control, no opening book, no EGTB and so on.
This is not meant as some sort of conspiracy theory on my part, I don't think there is a conspiracy of any kind, I just think that it is early days for this approach, interesting enough for Google to publish and get marketing on, and rather sloppy from a scientific standpoint because that's not their primary focus at the moment.
Now for my main point of this thread:
Many people (at least in comment threads on YouTube) seem to assume that AlphaZero just takes a look at the position and magically from its neural network gets the best move. They disregard the overwhelming significance of tactics in chess. And simply the shape and nature of the game tree itself.
Even if you have the best positional understanding in the world, you will still have to take tactics into account. Of course the notions of positional and tactical are only approximations. Until we have objectively solved chess, so-called positional understanding is only an approximation of the entire game tree from a given position. And tactics are the specific detailed discrete assessment that comes from applying this positional understanding to the (tiny) part of the game tree that you choose to visit in the allotted time. And for this, depth is still important no matter how you cut it. No matter what tree search algorithm you use. Note that I say depth and not nodes visited or nodes per second. If you somehow is very accurate in disregarding huge parts of the tree (which AlphaZero seems to be with its 80 knps) you can still look very deep into the most important variations. But this is a _tactical_ edge, not a positional edge as such.
In many of the games published, AlphaZero surely seems to have a better positional understanding. But in my opinion it would be impossible for it to win as comfortably as it did without also having a better tactical understanding, simply looking deeper into the important variations. In several of the games, AlphaZero _does_ make tactical moves that Stockfish seem to miss and by tactical I here mean moves that Stockfish would reasonably find by searching a little deeper. In my opinion there is a huge difference in an engine simply outsearching an opponent by looking a little deeper (which is not that impressive) and then in either looking a lot deeper (a real breakthough) or looking about as deep as the opponent but consistently so good positional understanding that the advantage eventually turns into inevitable tactics (also a breakthrough, but can only be useful if at the same time at least as tactically strong as the opponent).
It is unclear to be what was the case in these games.
Maybe AlphaZero just outsearched Stockfish a little bit. Just like Stockfish would against itself on better hardware. An engine outsearching another engine _will_ often look like better positional understanding.
Maybe AlphaZero looked a lot deeper, we don't know, there are no published search trees or variations or evaluations.
What _is_ a real breakthrough is the effectiveness of the selectivity of AlphaZero's approach, the small nps and hence size of the searched subtree. It is very impressive to _tactically_ play on par with or beat any recent version of Stockfish looking at only 80.000 nodes per second. To see deep enough in such a small number of nodes and still not make tactical errors for Stockfish to exploit.
It might not have been the positional understanding gained from deep learning and the neural network that made the difference. It could be tactical superiority from the effectiveness of the chosen tiny subtree to search.
Of course it is impressive and interesting whenever a chess engine beats (a version of) Stockfish 28/72/0, whenever a newer approach shows promise against and older approach, whenever a new engine comes up with novelties or a different style of play than most other engines and so on.
On the other hand, I think it is too early to conclude anything definite for a lot of reasons that have already been discussed: It is impossible at the moment for scientific peers to reproduce the results, it is impossible for peers to experiment with the engines in other ways, far from all games have been published, Stockfish had multiple handicaps such as hardware (I know it is hard to make a direct comparison between the hardware platforms, but AlphaZero relies heavily on specialized hardware at the moment and the combined (hardware/software) approach of AlphaZero is not as interesting as an approach that can readily be used on regular hardware, from smartphones to powerful PCs like competing approaches), older version, tiny hashtable, fixed time control, no opening book, no EGTB and so on.
This is not meant as some sort of conspiracy theory on my part, I don't think there is a conspiracy of any kind, I just think that it is early days for this approach, interesting enough for Google to publish and get marketing on, and rather sloppy from a scientific standpoint because that's not their primary focus at the moment.
Now for my main point of this thread:
Many people (at least in comment threads on YouTube) seem to assume that AlphaZero just takes a look at the position and magically from its neural network gets the best move. They disregard the overwhelming significance of tactics in chess. And simply the shape and nature of the game tree itself.
Even if you have the best positional understanding in the world, you will still have to take tactics into account. Of course the notions of positional and tactical are only approximations. Until we have objectively solved chess, so-called positional understanding is only an approximation of the entire game tree from a given position. And tactics are the specific detailed discrete assessment that comes from applying this positional understanding to the (tiny) part of the game tree that you choose to visit in the allotted time. And for this, depth is still important no matter how you cut it. No matter what tree search algorithm you use. Note that I say depth and not nodes visited or nodes per second. If you somehow is very accurate in disregarding huge parts of the tree (which AlphaZero seems to be with its 80 knps) you can still look very deep into the most important variations. But this is a _tactical_ edge, not a positional edge as such.
In many of the games published, AlphaZero surely seems to have a better positional understanding. But in my opinion it would be impossible for it to win as comfortably as it did without also having a better tactical understanding, simply looking deeper into the important variations. In several of the games, AlphaZero _does_ make tactical moves that Stockfish seem to miss and by tactical I here mean moves that Stockfish would reasonably find by searching a little deeper. In my opinion there is a huge difference in an engine simply outsearching an opponent by looking a little deeper (which is not that impressive) and then in either looking a lot deeper (a real breakthough) or looking about as deep as the opponent but consistently so good positional understanding that the advantage eventually turns into inevitable tactics (also a breakthrough, but can only be useful if at the same time at least as tactically strong as the opponent).
It is unclear to be what was the case in these games.
Maybe AlphaZero just outsearched Stockfish a little bit. Just like Stockfish would against itself on better hardware. An engine outsearching another engine _will_ often look like better positional understanding.
Maybe AlphaZero looked a lot deeper, we don't know, there are no published search trees or variations or evaluations.
What _is_ a real breakthrough is the effectiveness of the selectivity of AlphaZero's approach, the small nps and hence size of the searched subtree. It is very impressive to _tactically_ play on par with or beat any recent version of Stockfish looking at only 80.000 nodes per second. To see deep enough in such a small number of nodes and still not make tactical errors for Stockfish to exploit.
It might not have been the positional understanding gained from deep learning and the neural network that made the difference. It could be tactical superiority from the effectiveness of the chosen tiny subtree to search.