For example, the following two bitmaps are generated by a real random number generator and a PHP pseudo-random number generator under Windows. Moreover, the pseudo-random numbers may have a fixed period. The behavior of pseudo-random numbers is predictable, which means if we know the current state of the PRNG, we could get the next random number. PRNG’s result is random in a statistical sense. Please note that the RandSeed will be updated in each generation. I = (( double)RandSeed) / ( double) 0xffffffff Let’s have a look at Borland’s random number generator: long long RandSeed = 0xdeadbeaf // initialize a random seed
Pseudo-Random number generator (PRNG)Īs its name suggests, a pseudo-random number is not truly random in the strict mathematical sense and is generally generated by some mathematical formula (or a calculated table).įor example, a simple Linear congruential generator could be used to generate pseudo-random numbers. There are two types of random numbers generated by computers: truly random numbers and pseudo-random numbers, and each have their own advantages and disadvantages. Random number generationĪctually, there are some difficulties with generating random numbers only through computers.Ĭomputers are good at executing determinate tasks and run coded instructions according to the program. In this post, we will discuss how random numbers are generated, how to use random numbers to shuffle cards. Some classic randomized algorithms(such as Monte Carlo Algorithm) also rely on random number generation. Such as encryption keys, password generation, simulation, and games.
Random numbers represent uncertainty, which is widely used in the computing world.
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