army1987 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.

Comment author: [deleted] 18 October 2013 08:57:58AM *  0 points [-]

Too bad that the default PRNG in many systems is still an ancient one.

Comment author: V_V 18 October 2013 09:53:12AM 2 points [-]

Yes.
However, programming environments oriented towards numerical computing tend to use the Mersenne Twister as their default PRNG.

Comment author: [deleted] 18 October 2013 04:46:20PM *  0 points [-]

Mersenne Twister is the most commonly used algorithm. It is fast, and generates good results. It is not adversarial secure, but in that situation you should be using a cryptographically secure RNG.

Age of the PRNG algorithm has no bearing on this discussion. (If rand() uses something else, it's for standards-compatability reasons; nobody writing Monti-Carlo algorithms would be using such PRNGs.)

Comment author: [deleted] 19 October 2013 12:38:27PM 0 points [-]

If rand() uses something else, it's for standards-compatability reasons;

Actually the C and POSIX standard impose very few requirements on rand(); it would be entirely possible in principle for it to be based on the Mersenne Twister while still complying to the standards.

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