Hacker News new | ask | show | jobs
by mapt 3747 days ago
All AI does is remove the ability to progress through the ranks accurately via online play. Unregulated online competition will suddenly become a bumpy road full of Elo-breaking presences.

I gather this may be a Big Deal, but except insofar as it kills the sport by a thousand cuts, 'Young Go Prodigies' have nothing to worry about.

1 comments

The computer will be able to give you an Elo number just by looking at all the moves you did in a few games.

Since the computer can tell for every single move whether you played perfectly or if not, by how much you decreased your chances of winning against perfect competition, you'll be able to get a hundred signals out of a game into your elo calculation, instead of just one win/loss condition.

They already do that for catching cheaters in chess. In essence, you treat the positions that occur in a game not as a logical sequence, but as a series of multiple-choice questions.

Color me skeptical. The value of things like Elo is they provide a ramping scale with some degree of statistical significance, because they cover play over many games. I don't think a computer is going to be able to extrapolate with a high degree of confidence, because human play is variable from game to game and long-run strategies are non-obvious constructs for the computer.

You're thinking in terms of 'The AI has solved Go mathematically', but that's not the case; Just because you can run a Monte Carlo best-choice-picker/guesser algorithm doesn't mean you can meaningfully rank how deliberate choices compare with each other more than a few plays away.

Long-run strategies are a human crutch. It's easiest to see when you solved a game mathematically, that you can just value positions independently.

Go hasn't been solved to that level, but it's apparently been solved to higher level than humans ever reached.

I am just parroting http://www.uschess.org/content/view/12677/763 here, so I might as well quote:

"To catch an alleged cheater, Regan takes a set of chess positions played by a single player—ideally 200 or more but his analysis can work with as few as 20—and treats each position like a ques­tion on a multiple-choice exam. The score on this exam translates to an Elo rating, a score Regan calls an Intrinsic Perfor­mance Rating (IPR)."

This approach also allows to score historic players absolutely, instead of only relatively and trying to find sets of overlapping lifetimes until we reach the modern age.