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  2. Parody generator - Wikipedia

    en.wikipedia.org/wiki/Parody_generator

    (The term "quote generator" can also be used for software that randomly selects real quotations.) Further to its esoteric interest, a discussion of parody generation as a useful technique for measuring the success of grammatical inferencing systems is included, along with suggestions for its practical application in areas of language modeling ...

  3. Category:Random text generation - Wikipedia

    en.wikipedia.org/wiki/Category:Random_text...

    Pages in category "Random text generation" The following 19 pages are in this category, out of 19 total. This list may not reflect recent changes. A. AI Dungeon; B.

  4. Mersenne Twister - Wikipedia

    en.wikipedia.org/wiki/Mersenne_Twister

    The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by Makoto Matsumoto (松本 眞) and Takuji Nishimura (西村 拓士). [1] [2] Its name derives from the choice of a Mersenne prime as its period length.

  5. AutoNumber - Wikipedia

    en.wikipedia.org/wiki/AutoNumber

    AutoNumbers generated by this mechanism start with the start number and increment with the increment value, checking for collision with existing table rows. [2] random AutoNumbers generated by this mechanism are assigned using a pseudo-random number generator that generates long integers and checks for collisions with existing table rows. [2]

  6. Random seed - Wikipedia

    en.wikipedia.org/wiki/Random_seed

    A random seed (or seed state, or just seed) is a number (or vector) used to initialize a pseudorandom number generator.. A pseudorandom number generator's number sequence is completely determined by the seed: thus, if a pseudorandom number generator is later reinitialized with the same seed, it will produce the same sequence of numbers.

  7. Pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_number_generator

    It can be shown that if is a pseudo-random number generator for the uniform distribution on (,) and if is the CDF of some given probability distribution , then is a pseudo-random number generator for , where : (,) is the percentile of , i.e. ():= {: ()}. Intuitively, an arbitrary distribution can be simulated from a simulation of the standard ...

  8. Blum Blum Shub - Wikipedia

    en.wikipedia.org/wiki/Blum_Blum_Shub

    Blum Blum Shub takes the form + =, where M = pq is the product of two large primes p and q.At each step of the algorithm, some output is derived from x n+1; the output is commonly either the bit parity of x n+1 or one or more of the least significant bits of x n+1.

  9. Applications of randomness - Wikipedia

    en.wikipedia.org/wiki/Applications_of_randomness

    To illustrate, imagine if a simple 32 bit linear congruential pseudo-random number generator of the type supplied with most programming languages (e.g., as the 'rand' or 'rnd' function) is used as a source of keys. There will only be some four billion possible values produced before the generator repeats itself.