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Accuracy in Random Number Generation
The generation of continuous random variables on a digital computer encounters a problem of accuracy caused by approximations and discretization error. These in turn impose a bias on the simulation results. An ideal discrete approximation of a continuous distribution and a measure of error are proposed. Heuristic analysis of common methods for transforming uniform deviates to other continuous r...
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AI algorithms like genetic algorithms and automated opponents. Random game content and level generation. Simulation of complex phenomena such as weather and fire. Numerical methods such as Monte-Carlo integration. Until recently primality proving used randomized algorithms. Cryptography algorithms such as RSA use random numbers for key generation. Weather simulation and other stat...
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Introduction Random numbers play a large and significant role in several fields and applications from cryptography to gaming to gambling. As a result, random number generators (RNGs) occupy a similarly important role. By their very nature, however, random numbers are difficult to fabricate, especially in the large quantities that they are often needed. In this paper I will discuss various topic...
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ژورنال
عنوان ژورنال: Mathematics of Computation
سال: 1985
ISSN: 0025-5718
DOI: 10.2307/2008146