LYCOS RETRIEVER 
Pseudorandom Number Generator: Random Number Generators
built 811 days ago
Returns the next pseudorandom, uniformly distributed int value from this random number generator's sequence. The general contract of nextInt is that one int value is pseudorandomly generated and returned. All 232 possible int values are produced with (approximately) equal probability.
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"A nonperiodic random number generator, which is based on the logistic equation, is presented. A simple transformation that operates on the logistic variable and leads to a sequence of random numbers with a near-Gaussian distribution, is described and discussed. The associated algorithm can be easily utilized in laboratory exercises, classroom demonstrations, and software written for stochastic modeling purposes."
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Mathematicians have devoted a vast amount of time coming up with many pseudorandom number generation techniques. In the worlds of science and cryptography, it is important that a random number generator avoids repetition at any point and meets a stringent set of criteria. Luckily, most of things people do in flash don’t require this type of mathematical rigorousness.
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It is important to remember that a random number generator is not a "real" function like sine or cosine. Unlike real functions, successive calls to a random number generator yield different return values. Of course that is just what you want for a random number generator, but to achieve this effect, the generator must keep track of some kind of "state" variable. Sometimes this state is just an integer (sometimes just the value of the previously generated random number), but often it is more complicated than that and may involve a whole array of numbers, possibly with some indices thrown in. To use the random number generators, you do not need to know the details of what comprises the state, and besides that varies from algorithm to algorithm.
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Despite the fact that the Mersenne Twister is an extremely good pseudo-random number generator, it is not cryptographically secure by itself for a very simple reason. It is possible to determine all future states of the generator from the state the generator has at any given time, and either 624 32-bit outputs, or 19,937 one-bit outputs are sufficient to provide that state. Using a cryptographically-secure hash function, such as SHA-1, on the output of the Mersenne Twister has been recommended as one way of obtaining a keystream useful in cryptography.
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Returns the next pseudorandom, uniformly distributed boolean value from this random number generator's sequence. The general contract of nextBoolean is that one boolean value is pseudorandomly generated and returned. The values true and false are produced with (approximately) equal probability.
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Random Number Generators