[HN Gopher] Who is the most accurate world chess champion?
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Who is the most accurate world chess champion?
Author : piotrgrudzien
Score : 157 points
Date : 2021-12-02 09:18 UTC (2 days ago)
(HTM) web link (lichess.org)
(TXT) w3m dump (lichess.org)
| BlanketLogic wrote:
| > At the time of publishing, the last decisive game in the World
| Championship was game 10 of the World Championships 2016 -- 1835
| days ago, or 5 years and 9 days. Is the singularity being
| reached, with man and machine minds melding towards inevitable
| monochromatic matches?
|
| Very very unfortunate timing but still a valid question.
| ItsMonkk wrote:
| One of the reasons that Poker players prefer tournaments is
| because it induces them to move away from perfect Nash
| equilibrium play and into being exploitable, as someone who plays
| unexploitable play simply doesn't make it to the money as someone
| who does. Winning 51% of the time means nothing when you need to
| be in the top 10% to earn anything back.
|
| It seems like just looking at ACPL isn't looking at this
| correctly. If someone makes a mistake, and loses some centi-pawn,
| but it induces an even larger mistake in their competitor, that
| wasn't a mistake, it was a risk.
| mjw1007 wrote:
| Is there a risk that this measure is telling us as much about how
| likely a match was to contain difficult positions as about how
| skilled the players were?
|
| For example, Karpov and Kasparov sometimes agreed short draws. I
| wonder if that is flattering their figures.
| jeremyjh wrote:
| Definitely - if there are lots of good moves to be found
| accuracy will be higher. This is why when you analyze games for
| suspicion of cheating you cannot look only at the accuracy
| figure - you have to take into account how challenging the
| positions are. Lichess and chess.com both do this but they do
| not tell us how, for obvious reasons.
| freediver wrote:
| > Lichess and chess.com both do this but they do not tell us
| how, for obvious reasons.
|
| Isn't lichess open source?
| tromp wrote:
| I'm most impressed by Capablanca's jump in highly accurate play
| back in 1921, that would not be surpassed for another 60 years.
| pk2200 wrote:
| Capablanca preferred playing quiet, positional chess, often
| patiently nursing tiny endgame advantages into a win. It's
| generally much easier to play accurately in simple endgames
| than complex middlegames, and that's a big factor in his low
| ACPL score. (I don't mean to take anything away from him - he
| was probably the best ever at that style of play.)
| marvel_boy wrote:
| Capablanca without any doubt. Also Morphy.
| LudwigNagasena wrote:
| In part high accuracy means that the opponents are
| approximately of equal strength. The way people win games in
| chess is by complicating the position so much that it forces
| your opponent to make a mistake while you are able to handle
| it.
|
| If the accuracy is high, not only it means that the players are
| good, it also means that they don't ask each other serious
| questions. Put any human against Stockfish and, I am sure,
| their ACPL will increase dramatically.
| ummonk wrote:
| I'm not sure how meaningful these numbers are. I get around 40-50
| ACPL in my games, and I certainly wouldn't have been anywhere
| near a match for Botvinnik.
| LudwigNagasena wrote:
| Precision is a murky concept in chess because it is not a solved
| game. First, if the move doesn't change the best play result, can
| it really be called imprecise? Only in terms of practical
| chances.
|
| And if we are talking about practical chances, why should we rely
| on computer-centric evaluation? If a human has to choose between
| a move that leads to the win but they have to find 40 best moves
| or they will lose and a move that is a theoretical draw but now
| the opponent has to find 40 moves or they will lose, what should
| a human choose?
|
| What is even the ACPL of a move from a tablebase? There is no
| value, it is either a win, a draw or a loss. So while the whole
| idea behind this exercise is intuitively appealing and certainly
| captures some sense behind the idea of accuracy, it should be
| taken with a grain of salt.
| thom wrote:
| Yep, agree with this. It was surprising to me to find out how
| large the error bars were in computer evaluations of their own
| games. In the last TCEC superfinal, for example, the majority
| of the draws saw at least one position with an evaluation
| higher than +/-1.0, and 3 of the 26 decisive games came after a
| 0.0 evaluation. I assume that margin should be even bigger in
| human games, so it's hard to see what there is to learn
| (outside some fun lines) from looking at these numbers outside
| of opening prep.
|
| As for the tablebase question, it would be nice to see
| win/forced-draw probabilities from engines instead of the
| increasingly artificial material evaluation.
| Barrin92 wrote:
| >Precision is a murky concept in chess because it is not a
| solved game
|
| it's ironically also a murky concept for the opposite reason.
| In some openings the analysis of GM's goes so deep that they
| can fairly often play almost exclusively computer-aided prep.
| There's a big difference between a 40-move game in that kind of
| theoretical position vs off-beat games.
|
| Depending on the style of the players and how open the games
| are it gets pretty complicated to figure out what precision
| actually implies for the games in any real sense.
| [deleted]
| pgcj_poster wrote:
| I would have liked to see this go back far enough to include
| Morphy, whom Fischer considered "the most accurate player who
| ever lived." I would be surprised if Stockfish agreed, but it
| would be interesting to see.
| dfan wrote:
| Kenneth Regan's work on Intrinsic Performance Ratings includes
| estimated ratings for Morphy, which vary widely from event to
| event but average around 2300, which I think matches the
| intuitive perception of his strength that modern strong players
| have. https://cse.buffalo.edu/~regan/papers/pdf/Reg12IPRs.pdf
|
| (Of course, as with all historical players, he would be
| stronger if he were re-animated today and exposed to modern
| principles and openings.)
| nomilk wrote:
| Centipawn loss (or simply the engine's evaluation of a position)
| doesn't take into account how realistically a human could hold a
| position.
|
| During yesterday's WCC Game 6 the computer evaluation meant
| little when players were in time trouble. Anything could have
| happened going into the first time control, despite the game
| being dead drawn for the first 3.5 hours.
|
| In the final stages the computer again evaluated the game as
| drawn, but presumed Nepo could defend _perfectly_ for tens of
| moves without a single inaccuracy. Super GMs can 't do that given
| hours or days, let alone minutes.
|
| Last thought: did anyone else assume this was written in
| R/ggplot2 at first glance? Seaborn and/or matplotlib look
| strikingly like ggplot2 now days!
| 4by4by4 wrote:
| In my opinion, neural network engines like Alpha Zero or Leela
| Zero do a much better job of assessing how difficult a position
| is to hold. They also report the evaluation in a completely
| different manner, win/draw/loss probability as opposed to
| centipawn loss.
|
| For example, in yesterday's game Stockfish was often giving a
| drawn evaluation (0.00) where Leela Chess gave a win
| probability of 30%+. I was posting about this during the game.
|
| https://twitter.com/nik_king_/status/1466794534214504454?s=2...
| LudwigNagasena wrote:
| Stockfish also uses a neural network for evaluation.
| 4by4by4 wrote:
| True, it's works differently though. And Stockfish does not
| compute win/draw/loss probabilities as part of its eval. It
| converts cp to wdl using an exponential fit based stockfish
| vs stockfish games. So draw percentage in Leela is a lot
| more interesting and useful.
| ummonk wrote:
| Yes, but at its heart it's still classical alpha-beta
| search rather than monte carlo.
| polytely wrote:
| and exhaustion also starts to play a role after playing for
| like 7 hours, at some point mistakes will start to slip in.
| eckesicle wrote:
| I was thinking a bit about this during the game too.
|
| Perhaps alongside centipawn loss (a measure of how many
| hundredths of a pawn a player loses by making the non-optimal
| move as determined by a chess AI engine) we could also measure
| the difficulty of any position.
|
| Stockfish (a popular chess engine) roughly works by
| constructing a tree of possible moves and evaluating the score
| according to some heuristic at its maximum depth. The best
| result at depth n (25 I believe) is considered the best move
| and incurs 0 centipawn loss.
|
| Perhaps we can define the difficulty of a position by the
| relative centipawn loss at each preceeding depth in the tree?
| The difficulty of a position is then determined by the depth at
| which the best move no longer changes.
| ashtonbaker wrote:
| This is an interesting thought! A couple of other scattered
| thoughts I had about this:
|
| - Engine evaluation of a leaf of the tree will always be
| different and more sophisticated than human heuristics. So
| there's a problem where a human can't be expected to follow
| down some lines. Of course, this is always changing, as
| humans seek to understand engine heuristics better. Carlsen's
| "blunder" at move 33 was a good example of this, from my
| memory.
|
| - Maybe there's a difficulty metric like "sharpness", some
| function of the number of moves which do not incur a
| significant centipawn loss. Toward the end of game 6, Carlsen
| faced a relatively low sharpness on his moves, whereas
| Nepomniachtchi faced a high sharpness, and despite the
| theoretical draw, this difference will prove to be decisive
| between humans. This seems like it could interact in
| interesting ways with your difficulty metric - for example,
| what does it mean if sharpness is only revealed at high
| depth?
|
| - It would be interesting to take the tree generated by
| stockfish, and weight the tree at each node by the
| probability that a human player would evaluate the position
| as winning. Then you could give a probability of ending up at
| each terminal position of the tree. Maybe some sort of deep
| learning model trained on players previous games? Time
| controls add such a confounding factor to this, but it would
| be so interesting to see "wild engine lines" highlighted in
| real-time.
| Someone wrote:
| > In the final stages the computer again evaluated the game as
| drawn, but presumed Nepo could defend perfectly for tens of
| moves without a single inaccuracy.
|
| I agree that it's not very useful to compare with table bases,
| especially given the "30 seconds time added per move" regime
| this was played under by the time they reached the position.
|
| However, I don't think the table bases even have enough
| information to indicate how close to losing a theoretically
| drawn position is. So, i don't think this required perfect
| accuracy to defend against (defining 'inaccuracy' as any move
| for black that either makes it take longer to reach a draw or
| moves to a losing position. That, I think, is the most
| reasonable definition)
| jeremyjh wrote:
| You are definitely right about the evaluation; I switched
| between several streams and I don't think there was anyone
| saying that they didn't prefer white after around move 39,
| despite a 0.0 eval for a lot of those positions. But part of
| the reason the eval is misleading is because it might be
| reflecting a sequence of "only moves" - where only one move can
| hold that evaluation and it may be very hard to find some of
| those moves for black, while white has lots of good moves in
| each position. While that is a problem with human
| interpretation of eval, I do not see how it invalidates use of
| ACPL which is an average across the entire game.
| oneoff786 wrote:
| This is merely the seaborn "darkgrid" style option. You need to
| set it explicitly if you want this effect.
| nextaccountic wrote:
| Why isn't the time left of each player an input to the
| evaluator It shouldn't assume that everyone has plenty of time!
| 4by4by4 wrote:
| I've thought about this, too. Sadly, times only started being
| recorded in the last 20 years and last time I tried I
| couldn't find a large dataset with the times included.
|
| Chess.com did do one study and found a large percentage of
| mistakes occurs in moves 36-40 because in some time controls
| additional time is added at move 40.
| blt wrote:
| > _If we'd used a different chess engine, even a weaker version
| of the same one -- such as Stockfish 12 -- it may have found the
| 2018 World Championship the most accurate in history (assuming
| both players prepared and trained using Stockfish 12 in 2018)._
|
| This would be a really good follow-up experiment. If the
| theorized result really happens, we would have strong evidence
| that players are "overfitting" to their training chess engine. It
| would also be interesting to see how stable the historical
| figures look between different engines.
| KingOfCoders wrote:
| Yes "Alan Turing, was the first recorded to have tried, creating
| a programme called Turochamp in 1948."
|
| But also
|
| "Since 1941 Zuse worked on chess playing algorithms and
| formulated program routines in Plankalkul in 1945."
|
| https://www.chessprogramming.org/Konrad_Zuse
| umutisik wrote:
| If "accuracy" measures how well a player matches computer chess,
| then as players continue to study more and more with chess
| programs, you would expect their play to match the programs more
| and more.
|
| Personally I find it odd to measure how well the players match
| the computer program and call it accuracy. The computers do not
| open the game tree exhaustively so they give only one prediction
| of true min-max accuracy.
|
| When Lee Sedol made move 78 in game 4 against AlphaGo, it reduced
| his accuracy but won him the game.
| RockofStrength wrote:
| Move 78 was humanity's last great stand against AI in a board
| game. Lee Sedol, tired and inspired, reddens AlphaGo's ears
| with a move plucked from a higher dimension.
|
| It now seems humorous that Kasparov once accused people of
| helping computers behind the scenes. Now chess masters have
| been caught huddled in bathroom stalls with their smart phones.
| Chess commentators choose to willfully ignore chess engines in
| their presentations, in order to enable our understanding of
| the analysis. The torch has been passed.
| hyperpape wrote:
| We should be clear: move 78 didn't really work, except that
| the engine got confused. Other humans and later versions of
| Go engines can refute it.
| chki wrote:
| This is addressed in the article by the way.
| thepete2 wrote:
| I don't know if this is a thing, but chess players might also
| steer the game in a direction/position which their opponent
| hasn't studied much, but they have. There's a "social" side to
| this seemingly "mathematical" game, no?
| JulianWasTaken wrote:
| This is more so in the opening (the beginning of the game,
| and separately where engines tend to be a bit less
| informative) but yes it is definitely part of the chess
| metagame, and you'll often see commentators talk about
| whether someone is "still in prep" or has gotten out of it.
| It often can lead to time advantages if one gets an opponent
| out of prep.
| thom wrote:
| Fabiano Caruana (previous World Championship challenger) has
| said that he's happy to find lines where the machines have
| you slightly behind, purely because they're less like to have
| been studied in detail by your opponent. Even with perfect
| recall of the first 20/30 moves in various lines, players are
| still going to steer away from some lines based on their and
| their opponent's strengths (tough against super GMs with few
| weaknesses though). So you're definitely right, I think
| there's a lot of game theory here, albeit much of it settled
| by your team ahead of the actual match.
| oh_my_goodness wrote:
| It's strange how many times the article says 'chess software' has
| improved since (Turing's day, the 1990s, whenever). Sure, the
| software is better, but six orders of magnitude in hardware
| performance haven't hurt either.
| ummonk wrote:
| The hardware improvement has been huge, but on the other hand
| if you pit Stockfish NNUE against top 1990s software on equal
| modern hardware, Stockfish would win handily. It's really been
| both hardware and software improving.
| marcodiego wrote:
| Why not use something similar to alphago zero to carefully
| analyze chess games of a deceased player until it is able to
| mimic its decisions?
|
| It could bring many players "back to life". It would be even
| possible to watch "impossible matches" like Kasparov vs
| Capablanca!
| LudwigNagasena wrote:
| That seems like a complex problem. People don't play that many
| chess games in their life to get a dataset on the scale
| required for neural networks. You would need to train a general
| chess engine and then to tweak it using few-shot learning. But
| I doubt it could capture high level ideas behind player styles
| unless someone comes up with a smart architecture for that.
| leelin wrote:
| Chess.com has the "personality bots" that supposedly play with
| the style of various well-known players, streamers, and GMs.
|
| But I remember watching Hikaru Nakamura stream once playing
| through each of these bots (and beating them fairly easily). He
| commented that several of the bots were doing things the real
| players would never do, both in style and even the opening move
| (1.e4 for a player that almost always opens 1.d4)
|
| It was fairly early after the personality bots came out, so
| maybe they've fixed it by now.
| 8note wrote:
| My guess on the personality bots is that they set the bot to
| play at the players' current rating, not training ml based on
| the games.
| marcodiego wrote:
| Chessmaster 3k had that feature. But I was never good enough
| in chess to evaluate how well it worked. Still, I thought
| about the simplest method: - get a chess
| playing algorithm (I think it will probably well with minimax
| or mcts) with many tunables, - use a genetic
| algorithm to adjust the tunables of the first algorithm; use
| how similar it plays (make it choose a move on positions from
| a database of games from said player) as a goal function.
|
| Doesn't seem terribly complicated to do, but don't know how
| similar to a human it would play.
| thom wrote:
| You'd be training purely on games with outdated theory, in
| which case the engine would lose to those trained from more
| modern repertoires. Or you'd let it learn through self play
| after initially showing it the human games, in which case it
| would probably quickly lose the identifiable stylistic aspects
| of its initial training.
| csee wrote:
| The point isn't to make an unbeatable chess player, it's to
| 'bring them back to life'.
| thom wrote:
| But what I mean is Kasparov would destroy Capablanca. Even
| outside of what one might consider 'raw chess talent', he
| was drawing on decades of better theory and would deploy
| that knowledge. It would be hard to simulate Kasparov as if
| he were taught chess in Capablanca's time (maybe not
| impossible and a fascinating project, I just don't see how
| you'd do it).
| msbarnett wrote:
| > It would be hard to simulate Kasparov as if he were
| taught chess in Capablanca's time (maybe not impossible
| and a fascinating project, I just don't see how you'd do
| it).
|
| I don't think they were suggesting that's the result they
| wanted - if you could somehow magically reanimate
| Capablanca in real life and pit him against peak
| Kasparov, he might lose badly.
|
| A neural net having the same outcome is essentially
| what's being asked for. Kasparov raised on Capablanca's
| era chess or vice versa would be unrecognizably different
| players, and I don't think anybody expects an AI to
| simulate their soul.
| thom wrote:
| Fair enough. I don't think this is as interesting an
| experiment as people think though. Nobody wants to see
| Morphy on zero points but that's what would happen.
| thom wrote:
| I already want to take this back because Morphy probably
| would pick up points if we ran a tournament on the basis
| of all official and unofficial world champions, plus
| people with openings named after them. But the
| correlation between date of peak and performance would be
| extremely high.
| lisper wrote:
| Just in case you, like me, were wondering what the word
| "accurate" means in this context:
|
| https://support.chess.com/article/1135-what-is-accuracy-in-a...
| thom wrote:
| I think it would be worth looking at a player's accuracy in terms
| of their cohort's standard deviation, given that theory is more
| or less shared across all players. Even then, the best players
| now have the best teams and computers, so a lot of Magnus's
| accuracy in this game is a credit to Jan Gustafsson et al. I've
| been thinking how you might capture the player's accuracy out of
| their prep, that seems a better measure, but even then you're so
| often choosing between five +0.0 moves by the middle-game, and
| you could easily play many totally accurate moves if you didn't
| feel like agreeing a draw. I know some have looked at Markov
| models of a player's likelihood of a blunder to analyse this
| instead.
|
| Personally I've never felt Magnus enjoyed the modern game with as
| much opening preparation as we have now. It seems like he's only
| in the last few years invested the time in this, instead of
| relying on his technique to win even from losing positions. I
| hope AlphaZero proving that fun positional ideas like pawn
| sacrifices and h4 everywhere reinvigorated him somewhat during
| his dominant first half of 2019, so there's still hope the
| machines haven't just drained the romance from the game, even if
| their ideas remain dominant.
| hippodamos wrote:
| Sorry i am highjacking this thread. I am on a quest to find the
| rules of the chess variant finesse by GM walter Browne. If anyone
| knows them :
|
| https://lookingforfinesse.github.io/lookingforfinessevariant...
| raymondh wrote:
| For historical human-to-human games, it would be more interesting
| to see how well players targeted with weaknesses of their
| opponents. That skill likely mattered more than absolute accuracy
| as measured by computers.
| bjourne wrote:
| In chess ACPL roughly works like goals scored (conceded) in
| football. Goals are made when the defending team makes mistakes.
| A team that is a master of defense will concede few goals. But
| will also score few goals since defending well requires playing
| cautiously. Its the same with attacking, aggressive teams. They
| both score and concede more goals than the average.
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