Uri Blass wrote: ↑Wed Nov 24, 2021 7:16 am
I disagree and for me it is not understanding.
For me understanding is something that you can explain why and not hide behind the words:"neural network"
If your engine have a static evaluation of +3 for white and you have no idea why because from your point of view the position is equal then it is not a positional understanding from my point of view.
I hate seeing a huge score without understanding the reason for it and I believe that this huge score is not good from practical point of view because in a game there is a big probablity that the opponent will have no idea how to translate the huge score to victory so from my point of view old engines are better for analysis in many positions because they can give a move that they do not understand that it is losing so there is a good chance that the human opponent is not going to understand how to win and not the new engine that believe I am playing against super players and if everything lose can suggest me a move that gives no practical chances.
That is all equally applicable for any closed source engine, where the average user does not have any access to the source code of the engine. The evaluation function is still a black box, regardless of whether it uses a neural network or only handcrafted evaluation, and the average user simply cannot explain anything beyond hiding behind the words "evaluation function".
And that is even true of open source engines; most people do not have the time or resources to open Stockfish's source code and see how its evaluation function works, so for most people, the evaluation function is functionally a black box to them as well.
There are many positions that handcrafted evaluation using engines would evaluate at +3 but any semi-decent chess player would tell you is an equal position.
There is a big difference between a chess engine or chess player understanding a position and a user/developer understanding how the evaluation function works in an engine, and the former is far more important to the average chess player than the latter. Grandmasters these days like Carlsen, Caurana, and Dubov have all said at some point that after the top engines adopted neural networks, the engines were able to understand positions found in i.e. the French and the KID much better than before. No grandmaster cares about how Stockfish's handcrafted evaluation works.
My experience is that I have more misunderstanding of evaluations of the new engines.
With the old engines cases when the engine said +5 when I had no idea why were rare.
With the new engines cases when the engine say +5 when I have no idea why are common.
I suspect that if you want to predict result of a game between humans with fide rating of 2000 then evaluation of fruit2.1 after searching to depth 10 when you translate it to expected result is going to give you a better prediction than evaluation of the new engines regardless of depth and it may be interesting to check it.
As mvanthoor said, I think that has more to do with the fact that newer engines have stronger searches that allow it to search more deeply than older engines.
I think no and I can give examples for huge scores that I do not understand even at small depths.
[fen]r1b2rk1/bp3p2/p1pp1q1p/4pNp1/3PPnP1/1BP1BQP1/PP3P2/R4RK1 b - - 0 19[/fen]
Stockfish already see more than +3 at small depths when fruit does not see a decisive advantage for white.
From human point of view it is not an endgame material is equal and there are too many pieces on the board to be sure about something.
NN is holistic and doesn’t split its eval into positional and material. If you as human try and interpret it as a dichotomy, you’ll not get an understanding.
Secondly the eval doesn’t describe the position, it describes the position at the end of the PV, and the iterations 6,7,8,9 all show more or less the same thing. Black trades bishop for nite (gives up bishop pair), and can’t find anywhere good for his nite (if tries take on b2, nite gets trapped by Rd1d2. If retreats to g6 it gets hemmed in by the pawn structure and has no good squares. Exchanges in centre just cede white a big pawn centre. White has the beginnings of attack in king. Too many black problems, I agree with the NN, white win probably.
You maybe understand the position.
For me it was not clear that after Bxf5 gxf5 Ng6 white has a winning advantage.
Another example of position that I do not understand and I cannot explain by human terms how you can be so sure that black is winning after the wrong move is the following:
[fen]1r4k1/2p2p1p/3p2p1/p2P4/Pp1n1P2/1P4PP/2P3BK/4R3 w - - 0 32 [/fen]
White played the natural move Rc1 and it is a losing move but only from the super intelligent stockfish.
From a human point of view
I can see after enough thinking that Rc1 lose a pawn like other moves and probably not the best but not that it lose the game.
Uri Blass wrote: ↑Wed Nov 24, 2021 7:16 am
I disagree and for me it is not understanding.
For me understanding is something that you can explain why and not hide behind the words:"neural network"
If your engine have a static evaluation of +3 for white and you have no idea why because from your point of view the position is equal then it is not a positional understanding from my point of view.
I hate seeing a huge score without understanding the reason for it and I believe that this huge score is not good from practical point of view because in a game there is a big probablity that the opponent will have no idea how to translate the huge score to victory so from my point of view old engines are better for analysis in many positions because they can give a move that they do not understand that it is losing so there is a good chance that the human opponent is not going to understand how to win and not the new engine that believe I am playing against super players and if everything lose can suggest me a move that gives no practical chances.
That is all equally applicable for any closed source engine, where the average user does not have any access to the source code of the engine. The evaluation function is still a black box, regardless of whether it uses a neural network or only handcrafted evaluation, and the average user simply cannot explain anything beyond hiding behind the words "evaluation function".
And that is even true of open source engines; most people do not have the time or resources to open Stockfish's source code and see how its evaluation function works, so for most people, the evaluation function is functionally a black box to them as well.
There are many positions that handcrafted evaluation using engines would evaluate at +3 but any semi-decent chess player would tell you is an equal position.
There is a big difference between a chess engine or chess player understanding a position and a user/developer understanding how the evaluation function works in an engine, and the former is far more important to the average chess player than the latter. Grandmasters these days like Carlsen, Caurana, and Dubov have all said at some point that after the top engines adopted neural networks, the engines were able to understand positions found in i.e. the French and the KID much better than before. No grandmaster cares about how Stockfish's handcrafted evaluation works.
My experience is that I have more misunderstanding of evaluations of the new engines.
With the old engines cases when the engine said +5 when I had no idea why were rare.
With the new engines cases when the engine say +5 when I have no idea why are common.
I suspect that if you want to predict result of a game between humans with fide rating of 2000 then evaluation of fruit2.1 after searching to depth 10 when you translate it to expected result is going to give you a better prediction than evaluation of the new engines regardless of depth and it may be interesting to check it.
As mvanthoor said, I think that has more to do with the fact that newer engines have stronger searches that allow it to search more deeply than older engines.
I think no and I can give examples for huge scores that I do not understand even at small depths.
[fen]r1b2rk1/bp3p2/p1pp1q1p/4pNp1/3PPnP1/1BP1BQP1/PP3P2/R4RK1 b - - 0 19[/fen]
Stockfish already see more than +3 at small depths when fruit does not see a decisive advantage for white.
From human point of view it is not an endgame material is equal and there are too many pieces on the board to be sure about something.
NN is holistic and doesn’t split its eval into positional and material. If you as human try and interpret it as a dichotomy, you’ll not get an understanding.
Secondly the eval doesn’t describe the position, it describes the position at the end of the PV, and the iterations 6,7,8,9 all show more or less the same thing. Black trades bishop for nite (gives up bishop pair), and can’t find anywhere good for his nite (if tries take on b2, nite gets trapped by Rd1d2. If retreats to g6 it gets hemmed in by the pawn structure and has no good squares. Exchanges in centre just cede white a big pawn centre. White has the beginnings of attack in king. Too many black problems, I agree with the NN, white win probably.
You maybe understand the position.
For me it was not clear that after Bxf5 gxf5 Ng6 white has a winning advantage.
Another example of position that I do not understand and I cannot explain by human terms how you can be so sure that black is winning after the wrong move is the following:
[fen]1r4k1/2p2p1p/3p2p1/p2P4/Pp1n1P2/1P4PP/2P3BK/4R3 w - - 0 32 [/fen]
White played the natural move Rc1 and it is a losing move but only from the super intelligent stockfish.
From a human point of view
I can see after enough thinking that Rc1 lose a pawn like other moves and probably not the best but not that it lose the game.
White pawns are mostly fixed in wrong colour for the bishop. White has no passed pawn. The nite doesn’t need to worry about stopping a racing passed pawn and has multiple possible weaknesses to attack, it’s already an active nite. The bishop can’t do anything useful.
KN v KB is this case is very good for KN.
KRN v KRB also good for KRN, KNvKB is better though, so white has more problems if R exchanged. What can white do? Nothing at all. Lost.