Computers can do a lot of accurate brute-forcing; humans must see the position in a more holistic, intuitive way.

Excellent human players and excellent computer players are presumably doing completely different calculation tasks.

I would suggest that computers are still bad at approaching the task in a human-like way, but they will always be able to improve their method via Moore's law (at a minimum) where humans are stuck at their current level.

Stockfish might be able to tell you what it was doing, but not in a way that it would be reasonable for a human to follow.

What you are looking for is a teacher. You can pay for those ;) The closest we have got to a teacher app is perhaps a MOOC: not much computational progress has been made.

The neurological topiary for chess is strictly harder, because chess has fewer analogues in day-to-day experience.

Why do you need an AI? I don't play chess, but I suppose the above is more or less what an elite chess school provides, and you could likely reproduce it with books + practice + private lessons. That is, what Ericson calls deliberate practice and coaching.

Real players at each level tend to have characteristic weaknesses that are expressible in terms of the same factors used in a program's evaluation function. Consider some of the following, which players at a certain level will exhibit and then get past as they improve.

* Bringing the queen out too early.

* Missing pins and discoveries.

* Failing to contest the center.

* Creating bad bishops.

* Bad pawn structure.

* Failing to use the king effectively in the endgame.

These are all quantifiable. They could all be used to create a more realistic and satisfying opponent at 1200, 1500, 1800, etc. All it takes is some basic machine learning applied to a corpus of lower-level games, and a way to plug the discovered patterns into the playing engine.

the other problem is that the devs of the current top scrabble engines, quackle and elise, are (naturally) focused on getting better and better at playing, not on plausible ways to play badly. it's something i keep meaning to work on when i have some spare time; i have a few ideas, but nothing i've had the time to explore properly.

http://en.lichess.org/

[1] https://www.youtube.com/watch?v=7YWYS209ydE

An year ago Stockfish was near the top, but not quite there. Since then its development model became more open, and the open testing framework was introduced. The rate it's been adding Elo rating points since then has been amazing.

There is also a strong bias towards simplification, so if an evaluation feature is not proven to be an improvement it will be removed. Over the last few Stockfish versions, the # of lines has actually decreased in each version.

[1] http://en.wikipedia.org/wiki/Simultaneous_perturbation_stoch... [2] http://tests.stockfishchess.org/tests

Your comment seems either ignorant of the amount of work involved, or very arrogant about your skill, but does not provide any information for me to judge.

Why do you think you could beat even rybka with just six months of work?

Suppose you have a coin, which gives a random outcome X. But you can only observe the outcome of X when another independent binary random variable Y is true. How can you tell if X is biased? Since X and Y are independent, the observations where Y is false are irrelevant since they don't tell you anything about X. So you just keep the observations where Y is true, and from there you can apply a binomial statistical test to the observations of X.

[ In case you're wondering whether applying statistical tests to variable sample sizes is valid, the answer is yes: a p-value is a uniform random variable from the set of observables (augmented by a continuous random variable, since our set of observables is discrete) to [0,1]. Our p-value is a mixture of p-values on smaller sample sizes, so it is still uniform. ]

This is exactly what happens here: consider a random outcome {win,lose,draw}. If you don't have a draw, let Y be true and X be the outcome of the game. If you have a draw, let Y be false and X be a random coin with the same distribution as for non-drawn games. Then X and Y are independent random variables and the above applies.

Informally: draws are not useful information in determining whether there are more wins than losses.

The draws are at best evidence towards equality (not against it). Allow them to vary and the likelihood of seeing a difference of 9 wins in 64 games with 45 draws moves up to 0.13 or 13% (when we assume the two players are identical, an appropriate null hypothesis) (even less significant). So in about one tournament in 8 you would expect this much of a lead, even if it was one algorithm playing itself. So from one tournament we say it is likely the one algorithm is in fact better, but it doesn't rise to the standard of being statistically significant.

<code>

# R code to empirically estimate two-sided probablity of

# seeing a lead of 9 games when 64 games are played

# and the assumed probability of a draw is 45/64

# with the null assumption win/loss odds are equal

simulate <- function(nplay,ndraw) {

   sample(c('w','d','l'),size=nplay,replace=TRUE,

      prob=c((nplay-ndraw)/2,ndraw,(nplay-ndraw)/2)/nplay)

wldiff <- function(v) { abs(sum(v=='w')-sum(v=='l')) }

set.seed(350920)

stats <- replicate(10000,wldiff(simulate(64,45)))

print(sum(stats>=13-6)/length(stats))

## [1] 0.1341

</code>

(it is weird that somebody, not me, created a throw-away account to make the original comment. likely they are involved in chess development, or know how quickly stat discussions go sideways)

Is computer assisted chess a thing? Perhaps with standardized hardware, but any software.

In chess I'm good at strategy but terrible at calculating and I miss obvious stuff all the time in my fight for strategy. I always thought I'd do great with computer assistance to look for the obvious stuff, and me telling the computer the long term strategy.

> That either shows a profound understanding... or a profound lack of understanding. ... ROOK B6! He has NO SHAME

As far as I understand the app (whose avatar's age goes up to 23) actually plays better than the living world champion?

It's fantastic to see it take on the best commercial engines toe-to-toe and come out on top.

These ratings are computer ratings, and because they are playing very much isolates (computers vs other computers), without enough external human encounters, the ratings are consistent within the computer sphere, but not really like-for-like with human rating lists.

A lot has happened since Deep Blue - that was just a 6 game match, which really only proved that machines can play near a grandmaster level, but without nerves. And at times that is good enough to beat a world champion in match conditions, because the human is more susceptible to the psychological events.

Since Deeper Blue we've seen the emergence of chess engines on personal computers (rather than racks and racks of RS6000 mid-range servers), so Chess Genius, Fritz, Shredder, Junior, Rybka, Houdini and now Stockfish pushing chess engines ahead.

The Chess Genius - Junior levels show chess engines capable of matching grandmasters at blitz/active-play speeds, but still struggling at slower time controls.

Rybka onwards show a computer engine where elite grandmasters are seriously challenged.

Chess hasn't been solved. Just watching Magnus Carlsen's play shows we are expanding chess knowledge incrementally one game at a time. Yes, progress has slowed down, but the incremental improvement are still there.

Chess technique is refined to such a super high degree, but still far short of "solving chess". Perhaps this current generation can beat grandmasters when psychological factors are minimised, it's hard to tell.

It's certainly not as clear cut as a Porsche vs Usain Bolt over 100 meters.

1) Computer vs Computer can still go both ways so clearly the one chess engines make mistake others can exploit; 2) Some sequences are still hard find for computers, e.g. [1]. The long king walk by White is beyond the horizon of the computer. 3) Computer + Man against Computer + Man correspondence matches do benefit from human intervention.

[1]: http://www.chessgames.com/perl/chessgame?gid=1124533&kpage=5

For example, it may be reasonable to play an aggressive variation against an opponent because you think they might have difficulty finding a response in time pressure, but a computer can make precise calculations in any situation, and so such a strategy almost always backfires.

What's more, chess is often abstracted at higher levels in terms of things like long term plans ("I want to put pressure on the c7 pawn and control c6") instead of concrete material gains, which allows players to make progress even in positions where there are no direct threats and no sensible exchanges of pieces. Computers when faced with such situations will know that the position is objectively drawn and so will just shuffle their pieces around aimlessly, and playing against this kind of thing is not very good practice for actual human opponents who will try to find ways to beat you anyway.

Computers don't play like humans, and they are consistent in their weaknesses as well as their strengths. As players are more exposed to playing against various chess programs, they learn what positions computers are not so good at (long-range strategical themes, beyond the typical move horizon). A local optimisation, of sorts.

So players start adopting an anti-computer style of play, which requires a different mind set to pull off. That in turn affects their natural style of play.

So I argue the opposite, for preparing for top-flight tournaments, players probably avoid / severely limit playing against chess engines, to avoid this natural anti-computer bias to their play.

Sure, the engines are good for checking variations and analysis, as an assistant. But not as a leader, nor as an opponent.

In other words, modern humans have been playing in dull, more reliable ways for over a century, so even if not sore loserish, it's at least a bit like the pot calling the kettle black.