Question

I’m using the Mersenne twister algorithm to shuffle playing cards. Each time the deck needs to be shuffled I seed it with time(NULL) + deckCutCardNumber which is where the user chose to cut the deck. Would I get better results from only seeding it the first hand and continuing to generate them with the same seed or is this method more random?

Thanks

Answer 1

Assuming the user doesn’t mess with the clock (or carefully reduce their cut number by exactly the time that has passed), they’ll never see a repeated state of the PRNG anyway, so it doesn’t make much difference what you do. You’ll get a reasonable distribution out of the Mersenne Twister from any seed value[*], and at any feasible number of steps after re-seeding.

If you’re keen to reseed, though, you could combine both approaches by seeding with the time, plus the user-chosen number, plus an output taken from the generator just before reseeding. That combines (part of, not all) the current state of the PRNG with the new seed data, so to some degree all of the past times and cut values (and number of uses of the PRNG) can affect the state, not just the most recent. Pouring more information into the seed value in this way could be considered “more random” than a seed involving less information and hence fewer plausible values.

The only thing about Mersenne Twister in particular is that if you can observe 600-odd outputs of it, then you can deduce its internal state and predict the rest of the output until it’s reseeded. Then again, you probably wouldn’t use MT for an application where that sort of thing matters: if you’re relying on the reseed in any way then you should probably use a more secure PRNG to begin with. Clearly it doesn’t matter for your application if the user can predict the values out of the PRNG, since the user knows the time just as well as you do. All of this tells you that it shouldn’t matter how it’s seeded, just so long as it isn’t seeded with exactly the same value so that two games are identical. Hence it doesn’t matter whether it’s reseeded either.

[*] That’s not strictly true, there are classes of weak seeds for MT. But as long as you take that into account when seeding (for instance, hash the seed before use so that bad values are unlikely to crop up by chance), you work around that.