Abstract
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.
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Dumitrescu, M. (2012). On Degrees of Randomness and Genetic Randomness. In: Dinneen, M.J., Khoussainov, B., Nies, A. (eds) Computation, Physics and Beyond. WTCS 2012. Lecture Notes in Computer Science, vol 7160. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27654-5_8
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