Publication

Pseudo Random Numbers Generators available as Web Services

Sébastien Rumley
2008
Conference Papers

Abstract

Series of Pseudo Random Numbers are often used as simulation input, and they strongly Influence the results. Thus, their usage and the usage of their generator need to be taken care of very well. Qualified generators are available on the web as source code or libraries. However, they require an additional middleware to adapt them to the running environments, and this can lead to misuses.

Official source

https://infoscience.epfl.ch/entities/publication/940dfcd3-6712-48c8-b550-818148eb2068

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Sébastien Rumley
2008
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/940dfcd3-6712-48c8-b550-818148eb2068

About this result

Related concepts (12)

Pseudorandom number generator

A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG), is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by an initial value, called the PRNG's seed (which may include truly random values).

Random number generation

Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated. This means that the particular outcome sequence will contain some patterns detectable in hindsight but unpredictable to foresight. True random number generators can be hardware random-number generators (HRNGs), wherein each generation is a function of the current value of a physical environment's attribute that is constantly changing in a manner that is practically impossible to model.

Pseudorandomness

A pseudorandom sequence of numbers is one that appears to be statistically random, despite having been produced by a completely deterministic and repeatable process. Simply put, the problem is that many of the sources of randomness available to humans (such as rolling dice) rely on physical processes not readily available to computer programs. The generation of random numbers has many uses, such as for random sampling, Monte Carlo methods, board games, or gambling.

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