Basic principles of self-organization

Self-organization may be defined as a spontaneous process of development of an organized structure in open systems far from equilibrium. A slightly different definition is: “The evolution of a system from random initial conditions into an organized form in the absence of external pressures”. It may be taken as the opposite of construction.

Systems which are self-organizing acquire their new structure without specific interference from the outside. Starting from a random or homogenous state, large-scale patterns are spontaneously formed. There is no external influence or separate control unit that effects a change which may be of a spatial, temporal or functional nature. The process is irreversible, reflecting its chaotic and non-linear origin. It is organization without an organizer, coordinated without a coordinator. Things happen spontaneously without apparent cause, something which is called non- causality. Self-organizing system are said to be creative as new structures and models of behaviour are “invented”. All complex, self-organizing systems are adaptive as they try to turn what happens to their own advantage.

What all these complex self-organizing adaptive systems have in common is that they show a kind of dynamism that make them qualitatively different from “dead” systems which are only complicated. They are always in transition, unfolding with building block at one level combining to new building blocks at a higher level. Typical features characterizing self-organisation are:

  • No external control
  • Complexity
  • Instability
  • Fluctuations
  • Hierarchy building
  • Phase changes
  • Adaptation
  • Redundancy
  • Self-maintenance

Basically, it is a kind of evolution triggered by the system’s own inner dynamics. For self-organization to occur, the system must be neither too sparely connected with most units independent, nor too much connected so that every unit affects every other. In the system, the parts and components are interconnected in a nonlinear fashion by a complex network of feedback loops. From a mathematical point of view, this can be described by a set of nonlinear equations.

Complexity and order can arise, on its own, by self-organization from simple parts governed by rudimentary laws. Complexity and emergent properties occur when many of these components interact simultaneously. The complexity lies in the organization of the components. The evolution of self-organization normally exhibits a distinct and routinized path in a kind of repetitive, cyclical process.

First comes a long period of stability followed by a short period of strong fluctuations or chaos. From there the systems re-emerges to a new level of structural stability and order in a sudden jump called bifurcation. With this move, the previous and alternate steady states cease to exist. It has been followed by reorganization with more complexity and less redundancy.

In Figure 6.1, the chaotic stage, bifurcation, phase transition and the new steady state phases are shown.

A condition for self-organization is that the system is fed by high- value energy and exports entropy. Adding energy to a system, often in the form of heat, tends to drive it to a critical state, “on the edge of chaos” (Waldrop, 1992). It is the delicate balance between forces of order and forces of disorder. In “the edge of chaos”, one finds the complexity that makes life and mind possible. At this point, a small change can either push the system into chaotic behaviour or lock it into a fixed operation. When conditions are right, small chance events are magnified and building up gradually amplified by positive feedback. The energy contribution tunes the development of the system and gives something to react to. Once in a critical state, tiny perturbations may have enormous consequences and change the system in a moment under the influence of multiple positive feedback (see the butterfly effect, page 74).

Figure 6.1 Distinct phases of self-organization.

The result is often a phase transition to a new state with further hierarchical levels and increased complexity. Sudden sweeping changes are a key characteristic of systems at the critical point. At that point structure and interactions matter more than the properties of the elements in the system. An interesting fact is that critical systems seem to have a disproportionate number of large events, while less dramatic ones follow normal distributions.

In living systems, an ensemble of functions organize the enslaving of what will be a subsystem. It is released by internal variation processes or fluctuations starting at certain critical values of a system’s control parameters in which its components organize themself into a new pattern. It is a complex dynamic process emerging from one unorganized state to an organized one with time. The outcome is characterized by new, emergent properties transcending the properties of the constitutive parts at each new level of complexity.

Obviously the concepts of order and organization is associated with self-organization. A distinction between order and organization is that order is a pattern whereas organization is a process. Organization is also thought of as being for something. Order has to do with the quantity of information in a system, while organization defines the quality of that information. An ordered state increases the rate of entropy production and thus stress reduction. The greater the energy flows in a system, the greater the order. Generally, more ordered systems have better resilient to damage than less ordered ones.

Fluctuations can be demonstrated by a visual stimulus pattern according to Figure 6.2. During fixation, rosettes are created at various locations which in the next moment are decomposed.

Another quality of self-organization is autocatalytic or self- amplifying processes. They may be understood as simple feedback loops where the same operation is iterated or carried out repeatedly.

Figure 6.2 Continuous perceptual fluctuations in a visual pattern.

The formation of a self-organizing structure can be considered the opposite of a normal design process which basically proceeds from top down to bottom. Self-organized structures originates from bottom, leading to a hierarchy where higher levels show new qualities of the system. Although complex, the process may result from interactions among simple elements. Thus, macroscopic levels depend on microscopic interaction.

All self-organizing systems are open systems, by a continous influx of matter/energy and information. This implies that such systems are built against a surrounding disorder of much higher probability. Their emergence may be understood in a three level model according to the figures below, where the first visible stage of self-organization is a kind of spontaneous pattern formation, denoting rudimentary information processing. Consequently, systems which are unable to organize themselves exhibit no sign of information processes. Systems in balance or equilibrium, by definition, do not self-organize. Neither do chaotic systems which have no memory of the past. The system has to be in a critical state, just at the edge of chaos. Above this threshold, tiny changes can have very long-lasting effects.

When the critical point is attained, the properties of the individual elements cease to matter and the interaction take over. Once started, the process generates order, making use of energy for performing work, depreciates it and removes the resulting entropy. See Figure 6.3.

Figure 6.3 Emergence of order with energy/information flows.

In Figure 6.4, sensors and effectors has been created and self- reproduction occurs. Regulation by the use of feedback mechanisms exist.

The third level of the model is shown in Figure 6.5. Fiere advanced information processing takes place and a capacity for self-recreating exists. The system is regulated by sophisticated negative and positive feedback. Its stability is generated by reproducible relations among the component. This permits a withstanding of internal and external instabilities or disturbances.

Self-organization mainly take place episodically, in spurts, with intermittent bursts of activity, something defined as punctuated equilibrium. This process is possible only if the system has evolved to a complex critical state far from stability and take place over a long transient period without external influence. Sudden evolution, not gradual change, are typical for the emergent phenomena of self- organization.

How million of years with slow development was interrupted by intermittent burst of activity can be seen in the “Cambrian

Figure 6.4 Emergemce of order, self-reproduction and regulation

Figure 6.5 Emergence of order, self-reproduction, self-recreating and advanced regulation.

Explosion”. At that time, about 500 million years ago, a sudden proliferation of new species and families took place.

Systems approaching a complex critical state can, however, evolve into severe instability or catastrophe instead of a new organized structure. A general study of evolution shows that catastrophes are inevitable in biology, history, and economics. Even if we can explain with utmost precision what has happened earlier, we are not able to predict what will happen in the future. The same dynamics which produce small everyday events also give birth to large catastrophic happenings. Quite contrary to what is usually believed, large and dramatic events do not need a specific reason for their explanation. They take place without any outside intervention like extraterrestrial impacts. A meteor hitting the earth and causing one of the regularly occurring mass extinctions, merely represents a triggering event. The stage was already set in the previous history which had transformed the ecology into a critical state. A certain rate of mass extinction seems to be essential for evolution. “Without death there is no progress”.

Source: Skyttner Lars (2006), General Systems Theory: Problems, Perspectives, Practice, Wspc, 2nd Edition.

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