MARKOV CHAIN
| Collection | International Encyclopedia of Systems and Cybernetics |
|---|---|
| Year | 2004 |
| Vol. (num.) | 2(1) |
| ID | ◀ 2007 ▶ |
| Object type | Methodology or model |
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, p.47).
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).