I am looking for a way to generate pseudo random number sequences that will yield identical sequence results for a given seed across any platform. I am assuming that rand()
/ srand()
is not going to be consistent (I could easily be wrong about this assumption).
Methods of sampling a non-uniform distribution are typically based on the availability of a pseudo-random number generator producing numbers X that are uniformly distributed.
The outcome of the research confirms the possibility that machine learning algorithms can be trained to predict certain PRNGs. Even when trained with a small amount of data, there is evidence that machine learning algorithms can be used to predict the values created by pseudorandom number generators.
Widely used PRNG algorithms : Lagged Fibonacci generators, linear feedback shift registers, Blum Blum Shub.
Something like a Mersenne Twister (from Boost.Random) is deterministic.
Knuth has released into the public domain C (and FORTRAN) source code for the pseudo-random number generator described in section 3.6 of The Art of Computer Programming.
I realize this is an old thread but now with C++11 there are a whole bunch of new options available. Here is a distilled example from the page which defaults to using the Mersenne Twister
engine and Normal
distribution:
#include <iostream>
#include <iomanip>
#include <string>
#include <map>
#include <random>
int main()
{
std::random_device rd;
//
// Engines
//
std::mt19937 e2(rd());
//std::knuth_b e2(rd());
//std::default_random_engine e2(rd()) ;
//
// Distribtuions
//
std::normal_distribution<> dist(2, 2);
//std::student_t_distribution<> dist(5);
//std::poisson_distribution<> dist(2);
//std::extreme_value_distribution<> dist(0,2);
std::map<int, int> hist;
for (int n = 0; n < 10000; ++n) {
++hist[std::round(dist(e2))];
}
for (auto p : hist) {
std::cout << std::fixed << std::setprecision(1) << std::setw(2)
<< p.first << ' ' << std::string(p.second/200, '*') << '\n';
}
}
I've been working on a simplerandom
library for this. It is supposed to be cross-platform, and I also aim to target multiple languages. Currently it supports C and Python (same numbers generated in both languages). I plan to implement the same generators in C++ soon, following the Boost and C++11 random API.
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