Not really, humans barely provide insight (if anything), which chess engines don’t already consider. Deep Blue could evaluate 200 million different moves... per second. And that’s from 1997.
The few and rare times an engine gets funky is usually in end-game positions where the engine can’t seem to find a sacrifice to win the game and will output a current position as drawn. These cases are few and I very much doubt that a human would be able to find these moves in an actual match.
Now if you’re talking about the way the chess engine learns, it can learn in two different ways: without human help (learning completely on its own giving it nothing but the rules which is how AlphaGo works), or with human aid (through chess theory accumulated over centuries of human matches that these engines have built in as part of their evaluations). Things get very interesting.
I’d recommend you to look up a few games between AlphaGo and Stockfish, which embody these two different philosophies and battle it to the teeth and bones. The matches are brilliant. I would say though that it seems like AlphaGo (learning the game entirely through scratch without human help) has seemed to triumph more times than Stockfish and with the nature of these systems, I’d suspect it to continue that trend.
I'm not sure it's right to characterise Deep Blue or Stockfish as repositories of human chess theory. Fundamentally they were all based on a relatively simplistic function for calculating the value of a board position combined with the ability to evaluate more board positions further into the future than any human possibly could (plus a database of opening moves). That approach seems thoroughly non-human, and represents a victory of tactical accuracy over chess theory or strategy.
However I agree that the games between AlphaGo and Stockfish are really interesting. It strikes me that the AlphaGo version of chess looks a lot more human; it seems to place value on strategic ideas (activity, tempo, freedom of movement) that any human player would recognise.
I think you're right, I meant to say that chess engines usually have book openings built into them which derive off of human chess theory but you're absolutely right in that they don't play in a human form.
It's kind of crazy how AlphaZero has managed the success it has. Stockfish calculates roughly 60 million moves per second and AlphaZero calculates at only 60 thousand per second. Three orders of magnitude less yet its brilliance is mesmerizing, tearing Stockfish apart in certain matches.
> ...learning completely on its own giving it nothing but the rules which is how AlphaGo works...
Not to be too picky, but it was AlphaGo _Zero_ that learned from the rules alone. AlphaGo learned from a large database of human played games: "...trained by a novel combination of supervised learning from human expert games". [1]
AlphaGo Zero, derived from AlphaGo, was "an algorithm based solely on reinforcement learning, without human data, guidance or domain knowledge beyond game rules". [2]
And some of the most amazing games are when AlphaGo is absolutely breaking chess "wisdom" left and right simply because it can see a forced solution on the horizon.
The few and rare times an engine gets funky is usually in end-game positions where the engine can’t seem to find a sacrifice to win the game and will output a current position as drawn. These cases are few and I very much doubt that a human would be able to find these moves in an actual match.
Now if you’re talking about the way the chess engine learns, it can learn in two different ways: without human help (learning completely on its own giving it nothing but the rules which is how AlphaGo works), or with human aid (through chess theory accumulated over centuries of human matches that these engines have built in as part of their evaluations). Things get very interesting.
I’d recommend you to look up a few games between AlphaGo and Stockfish, which embody these two different philosophies and battle it to the teeth and bones. The matches are brilliant. I would say though that it seems like AlphaGo (learning the game entirely through scratch without human help) has seemed to triumph more times than Stockfish and with the nature of these systems, I’d suspect it to continue that trend.