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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 ...
Random numbers have uses in physics such as electronic noise studies, engineering, and operations research. Many methods of statistical analysis, such as the bootstrap method, require random numbers. Monte Carlo methods in physics and computer science require random numbers. Random numbers are often used in parapsychology as a test of precognition.
Good's authorship of treatises such as his 1965 "Speculations Concerning the First Ultraintelligent Machine" [17] and "Logic of Man and Machine" [18] made him the obvious person for Stanley Kubrick to consult when filming 2001: A Space Odyssey (1968), one of whose principal characters was the paranoid HAL 9000 supercomputer. [3]
The RA-machine's equivalent of the universal Turing machine – with its program in the registers as well as its data – is called the random-access stored-program machine or RASP-machine. It is an example of the so-called von Neumann architecture and is closest to the common notion of a computer .
While a monkey is used as a mechanism for the thought experiment, it would be unlikely to ever write Hamlet, according to researchers.. The infinite monkey theorem states that a monkey hitting keys at random on a typewriter keyboard for an infinite amount of time will almost surely type any given text, including the complete works of William Shakespeare.
Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols is generated that cannot be reasonably predicted better than by random chance. This means that the particular outcome sequence will contain some patterns detectable in hindsight but impossible to foresee.
In theoretical computer science and cryptography, a pseudorandom generator (PRG) for a class of statistical tests is a deterministic procedure that maps a random seed to a longer pseudorandom string such that no statistical test in the class can distinguish between the output of the generator and the uniform distribution.
Make the wall a passage and mark the unvisited cell as part of the maze. Add the neighboring walls of the cell to the wall list. Remove the wall from the list. Note that simply running classical Prim's on a graph with random edge weights would create mazes stylistically identical to Kruskal's, because they are both minimal spanning tree algorithms.