MARKOV CHAIN 2)
A sequence of neither purely random, nor purely deterministic transitions from one state to any other in a system.
Another interesting definition by K. KRIPPENDORFF: "The behavior of an informationally closed and generative system that is specified by transition probabilities between the system's states" (1986, p47).
He adds: "The probabilities of a MARKOV chain are usually entered into a transition matrix indicating which state or symbol follows which other state or symbol. The order of a MARKOV chain corresponds to the number of states or symbols from which probabilities are defined to a successor. Ordinarily, MARKOV chains are state determined, or of the first order. Higher orders are history determined. An unequal distribution of transition probabilities is a mark of a MARKOV chain's redundancy, and a prerequisite of predictability" (Ibid)
I. PRIGOGINE and I. STENGERS state the three general characteristics of Markov chains: "Non-repetitivity, existence of long range correlations and spatial symmetry breaks" (1992, p.90).
Markov chains are "statistically reproductive" and correspond to deterministic chaos "intermediary between pure randomness and redundant order" (Ibid).
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Bertalanffy Center for the Study of Systems Science (2020). Title of the entry. In Charles François (Ed.), International Encyclopedia of Systems and Cybernetics (2). Retrieved from www.systemspedia.org/[full/url]
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