Information and Randomness: An Algorithmic Perspective
Information and Randomness: An Algorithmic Perspective
Entropic measures, Markov information sources and complexity
Applied Mathematics and Computation
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This essay is inspired by Cristian Calude's view on degrees of randomness, in relation with "algorithmic randomness". As a "probability person", I am interested in "probabilistic randomness", which can be considered, within the omnipresent uncertainty, only in relation with a real phenomenon/source. Both approaches would produce a characterization of "randomness", as well as a hierarchy of randomness sources. The degree of adequacy for probabilistic randomness can only be evaluated by statistical procedures and it will serve for reliable predictions--which represent the goal of the science "stochastics", as stated by Jakob Bernoulli in the beginning of the18th century. Quantum randomness, produced by a natural source, can only be evaluated in a relative way, when compared with randomness produced by non-quantum sources. Genetic randomness represents the probabilistic randomness of the actual, observable source of genetic information, DNA. A degree of adequacy should be considered in this case, as expressing the degree the probabilistic model observes the variability and allows reproducibility of the real phenomenon. Such a degree of adequacy can be evaluated by statistical procedures.