PROCESSES (A taxonomy of)
| Collection | International Encyclopedia of Systems and Cybernetics |
|---|---|
| Year | 2004 |
| Vol. (num.) | 2(2) |
| ID | ◀ 2658 ▶ |
| Object type | General information, Methodology or model |
This is no more than a tentative taxonomy based on different descriptions of processes made independently by various authors.
- Causal process: “A process such as, if the state of system is exactly known in a given moment, it becomes possible to univocally determine its state in a future instant”.
This definition by V. TONINI (1971, p.227), related to Laplacian view of determinism, is obviously theoretical. While all processes are necessarily causal, their perfect knowledge at any moment is impossible.
- Chaotic process: A process proper to any complex system with sensibility to its initial conditions.
A chaotic process remains basically deterministic, but its development is not precisely predictable, as it turns generally probabilistic, within fuzzily determined channels.
- Cybernetic process: “A process submitted to regulations aiming at the elimination of unfavorable probabilities and optimize the favorable ones” (TONINI, p.229).
This is the classical control process of N. WIENER.
- Cyclical process: A process in which interconnected, but different regularities lead to periodic oscillations.
This type of processes is a typical result of any endogenously or exogenously generated constraint. There are various types of cyclical processes, as:
- cyclical with progressively damped oscillations, resulting from the dominance of the negative feedback over the positive one. It may lead to the destruction of the system by blockage.
- cyclical with progressive amplified oscillations, a result of the dominance of the positive feedback which can lead to the destruction of the system or to dissipative structuration and the possible emergence of a more complex system.
- Ergodic process: A succession of states of a system which depens directly form its most recent state, but also in a stochastic way from a transitions probability matrix which reflects the more or less lax general constraints on the system.
- linear process: A monotonous process in which a same quantitative cause produces a same corresponding quantitative effect.
- logistic process: A process in which a first period of nonlinear growth is succeded by an also nonlinear decelerating period.
A logistic process can lead either to an aymptotic limit, or to a more or less strong relaxation oscillation.
- nonlinear process: A process in which an accumulative cause (geometric, exponential, hyperbolic or logarithmic), or a feedback leads to non-monotonous increasing or decreasing effects.
If not regulated, nonlinear processes lead to deep changes in systems and, sometimes to their destruction or mutation.
- Stochastic process: “A process that produces a series of symbols in accordance with certain probabilities” (C. SHANNON, 1949).
Replacing “symbols” by “effects” this communication theory definition can be considerably extended.
Stochastic processes allow for global forecasts, but not about any specific determined behavior.
- Undetermined process: “A process for which no perfect knowledge of the original state of the system is possible” (TONINI, p.228).