3 ms·

Calling it "pseudo-Monte Carlo" is like calling a landline phone a "wired cell phone". It kind of misses the point.

retroencabulato 12y ago
No, you missed the point. In problems with a very large sample space, quasi-MC methods are invaluable. They converge faster and can be shown to approximately have the benefits of traditional MC methods.
- wfunction 12y ago
  I think we're talking past each other here. Talking about "sample space" inherently assumes you're dealing with a random process. My point is pi isn't random, so coming up with a random process just so you can force MC on it and then suddenly deciding you want to make it deterministic just so you can call it "pseudo-MC" is kinda... weird, to say the least. I really wish people would stop trying to find ways of calling their algorithms "Monte Carlo" just to make their work sound fancy. All it really achieves is it makes them avoid thinking about how to solve the problem. Monte Carlo isn't a universal hammer. First you're supposed to show randomness actually helps you gain something, then you're supposed to start using it.
  - jacquesm 12y ago
    I think there is some value to this method, but it may not be readily apparent in the present context. If you have a problem that you don't yet have a firm theoretical handle on you can figure out a baseline value for the answer using this technique, and then work backwards to give you the formula that allows you to arrive at the real answer. I use that trick a lot, for instance with Euler problem 307 I could not find the answer easily in an analytical way, did the simulation, found an approximate answer (to within 6 decimal places or so), used that to figure out what I was doing wrong and then computed the real answer. Some may see that as cheating, but it works wonders and not just on that particular problem.
    - wfunction 12y ago
      I've done that too, and I think there's nothing wrong with that. All I'm saying is people should stop calling it Monte Carlo once they've found the correct solution and realized it has nothing to do with randomness.

No, you missed the point. In problems with a very large sample space, quasi-MC methods are invaluable. They converge faster and can be shown to approximately have the benefits of traditional MC methods.

wfunction 12y ago
I think we're talking past each other here. Talking about "sample space" inherently assumes you're dealing with a random process. My point is pi isn't random, so coming up with a random process just so you can force MC on it and then suddenly deciding you want to make it deterministic just so you can call it "pseudo-MC" is kinda... weird, to say the least. I really wish people would stop trying to find ways of calling their algorithms "Monte Carlo" just to make their work sound fancy. All it really achieves is it makes them avoid thinking about how to solve the problem. Monte Carlo isn't a universal hammer. First you're supposed to show randomness actually helps you gain something, then you're supposed to start using it.
- jacquesm 12y ago
  I think there is some value to this method, but it may not be readily apparent in the present context. If you have a problem that you don't yet have a firm theoretical handle on you can figure out a baseline value for the answer using this technique, and then work backwards to give you the formula that allows you to arrive at the real answer. I use that trick a lot, for instance with Euler problem 307 I could not find the answer easily in an analytical way, did the simulation, found an approximate answer (to within 6 decimal places or so), used that to figure out what I was doing wrong and then computed the real answer. Some may see that as cheating, but it works wonders and not just on that particular problem.
  - wfunction 12y ago
    I've done that too, and I think there's nothing wrong with that. All I'm saying is people should stop calling it Monte Carlo once they've found the correct solution and realized it has nothing to do with randomness.