bogdanb comments on The Weighted Majority Algorithm - Less Wrong

18 Post author: Eliezer_Yudkowsky 12 November 2008 11:19PM

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Comment author: [deleted] 14 July 2013 08:22:44AM 3 points [-]

(I have a vague recollection of an anecdote about MCI: Someone somewhere was using it to do a complicated multiple integral, and got very silly results. Turns out, while the pseudo-random generator looked OK by itself, when its output was distributed throughout the complicated multi-dimensional space that was sampled, a non-obvious regularity in the generated numbers happened to match something the function did. So, in effect, the function beat them. In other words (ignoring that this is apocryphal), you don’t even need a very smart opponent to be screwed, a hard function is enough... That quantum noise generator can be very handy.)

Modern PRNGs tend to be less bad than that.

Comment author: bogdanb 14 July 2013 01:28:20PM *  2 points [-]

That’s not at all my domain of expertise, so I’ll take your word for it (though I guessed as much).

That said, I meant that as half funny anecdote, half “it’s not just theory, it’s real life, and you can get screwed hard by something that guesses your decision algorithm, even if it’s just a non-sentient function”, not as an argument for/against either MC or quantum noise. (Though, now that I think of it, these days there probably are quantum noise generators available somewhere.)

Comment author: [deleted] 14 July 2013 02:23:22PM 2 points [-]

(Though, now that I think of it, these days there probably are quantum noise generators available somewhere.)

AFAIK, there are but they're way too slow for use in MC, so decent-but-fast PRNGs are still preferred.

Comment author: [deleted] 10 December 2013 11:55:09AM 0 points [-]

Also, sometimes you need to run several tests with the same random sequence for debugging purposes, which with true random numbers would require you to store all of them, whereas with pseudo-random numbers you just need to use the same seed.

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