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  2. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. 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.

  3. Generator (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Generator_(mathematics)

    Generator (mathematics) The 5th roots of unity in the complex plane under multiplication form a group of order 5. Each non-identity element by itself is a generator for the whole group. In mathematics and physics, the term generator or generating set may refer to any of a number of related concepts. The underlying concept in each case is that ...

  4. Diffie–Hellman key exchange - Wikipedia

    en.wikipedia.org/wiki/Diffie–Hellman_key_exchange

    The generator g is often a small integer such as 2. Because of the random self-reducibility of the discrete logarithm problem a small g is equally secure as any other generator of the same group. If Alice and Bob use random number generators whose outputs are not completely random and can be predicted to some extent, then it is much easier to ...

  5. Random permutation - Wikipedia

    en.wikipedia.org/wiki/Random_permutation

    A random permutation is a random ordering of a set of objects, that is, a permutation -valued random variable. The use of random permutations is common in games of chance and in randomized algorithms in coding theory, cryptography, and simulation. A good example of a random permutation is the fair shuffling of a standard deck of cards: this is ...

  6. Maze generation algorithm - Wikipedia

    en.wikipedia.org/wiki/Maze_generation_algorithm

    Maze generation animation using a tessellation algorithm. This is a simple and fast way to generate a maze. [3] On each iteration, this algorithm creates a maze twice the size by copying itself 3 times. At the end of each iteration, 3 paths are opened between the 4 smaller mazes.

  7. Fisher–Yates shuffle - Wikipedia

    en.wikipedia.org/wiki/Fisher–Yates_shuffle

    However, the need in a Fisher–Yates shuffle to generate random numbers in every range from 0–1 to 0–n almost guarantees that some of these ranges will not evenly divide the natural range of the random number generator. Thus, the remainders will not always be evenly distributed and, worse yet, the bias will be systematically in favor of ...