Technological systems become organised by commands from outside, as when human intentions lead to the building of structures or machines. But many natural systems become structured by their own internal processes: these are the self-organising systems, and the emergence of order within them is a complex phenomenon that intrigues scientists from many disciplines (Yates et al., 1987, cited in Camazine et al., 2001).
Self-organisation is a process that is set in motion when, confronted with change, components of a system (e.g. individuals, organisms, elements) spontaneously form patterns and structures in order to target their goals: problem-solving. One way of understanding self-organisation is to contemplate a common purpose or problem, initiating a strong relocation of energy and actions within a system, which leads to the formation of complex webs from elements that are sparsely coupled in order to achieve a common purpose. Following are four definitions that summarise the view of self-organisation as it is being used in this paper:
Self-organisation refers to a broad range of pattern-formation processes in both physical and biological systems, such as sand grains assembling into rippled dunes, chemical reactants forming swirling spirals, cells making up highly organised tissues, and fish joining together in schools (Camazine et al., 2001).
Self-organisation literally denotes the process whereby a group of people organise themselves in pursuit of a common cause (Humphrey, 2000).
[Self-organisation is] the flexibility of a system to deal successfully with variety in transactions with the environment (Molleman, 1998).
Self-organisation is an emergence of order to deal with social complex systems (Yates et al., 1987).
The term, pattern, as used in this paper, denotes a particular organised assembly of elements taking place in a specific space and time. Based on local information, a system’s components interact to create a pattern. As such, a pattern’s formation is built with no external direct influence; that is, with no global information or directions from a leader. Patterns, from Kauffman’s (1995) point of view, are the creation and physical representation of order; while order is then accounted to the theory of emergence as one of its creations. He argues that order arises naturally as an expression of the self-organisation that abounds in very complex networks. Similarly, in social systems and organisations, the formation of clusters by people themselves pursuing a common cause is a clear example of self-organising patterns.
Rycroft and Kash (2004) state that the world is full of self-organising systems that form structures and processes in response to their own internal logic. A review of the literature (see, for example, Kauffman, 1993; Comfort, 1994; Hudson, 2000; Camazine et al., 2001) suggests that these types of systems have three basic components. Holland and Melhuish (1999) more specifically point out there are three distinctive signatures that complement the four basic characteristics of self-organisation. The three signatures are:
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the creation of spatio-temporal structures;
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the possible attainability of different stable states (multiple stable interactions within a system or parallel-processing systems, where various components perform various functions concurrently in order to achieve a desired outcome); and
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the capacity for adaptation to the prevailing environment.
Self-organisation is a problem solving process whereby components or elements at one particular level interact in order to create structures at a higher level, which may combine again to create even higher level structures. The structures emerging from these repeated interactions develop patterns that are then recognised as self-organisation. Jointly with the environment’s space and time, they define the first signature of self-organisation: spatio-temporal structures. An example commonly cited is the spatio-temporal patterns of army ant raids. The coordinated, functional structure of their movement, which spontaneously forms a higher order structure, occurs with minimum external interference.
Self-organisation takes place in systems with multiple active interactions among many actors. Because there are many, often identical, actors there is no requirement for a single actor (e.g. a leader) to carry out a series of connected sequences of movements. For example, referring to an army of ants foraging without recruitment, the rules of thumb [1] are just simple cues that alone will ensure that a complete sequence of actions is executed, even though an action or movement may be performed by a different ant from the one initially involved in it. The execution of these rules, in this case, is conducted by the flow (cue) of an ant’s pheromone. Multiple stable interactions arise when other ants interact with this cue and create new stimuli for further interactions to occur.
Ants leave their nest in order to find food. Once found, they load up and return to the nest leaving a trail of pheromone. For simplicity, assume that ants ‘would raise an alarm for other ants to follow’; while this is a multiple interactive process, it could also be a parallel-process as other ants from the nest may find other food sources and also raise an alarm. However, as Holland and Melhuish (1999, p. 4) assert, ‘… if there are many locations with such cues, the subtask [2] will be performed faster at the location that has greatest numbers of agents present’ due to the higher interaction rate and stability of the process.
Prigogine (1996, p. 711) argues that ‘… self-organising systems allow adaptation to the prevailing environment’. Comfort (1994, p. 3) explains that:
… self-organisation recognises that individual choices, communicated across organisational frameworks, affect the operation of the wider system [and] in this respect, voluntary selection allows individuals operating within organisational systems to cluster around points of energy that they find more attractive, creating a ‘peak’ of energy distribution over repeated interactions and aligning other members to that point in a ‘basin’ of attraction.
This explains why ants perform faster at the location that has greatest numbers of ants present: they cluster around the point of more attractive energy, adapting to environmental conditions (Kauffman, 1993; 1995). This actually becomes a powerful mechanism when coupled with one of the formal characteristics of self-organisation: positive feedback.
In summary, self-organisation is the result of utilising the system’s capacity for patterns and structure formation; processing communication and multiple interactions by choices or cues; and the mutual adjustment in behaviour based on a shared goal among actors of a given system and environmental conditions. Based on these signatures, we can now start to identify the main four characteristics of that system.
While most self-organising systems use positive feedback, for such systems both negative and positive feedback are indispensable. Camazine, et al. (2001) point out that negative feedback often takes the form of regulation, competition, reduction or saturation. Continuing with the social insect analogy: in the ants’ nest negative feedback dominates when there is competition among food sources, the food source is fully consumed, too many ants are feeding from a food source, there are not enough food sources in a particular area, lack of space or any other similar event that overtakes the positive feedback processes of the ants’ nest. Consequently, the ants are forced to hunt for other food sources and commence the feeding cycle again. A different example used in the biology literature is the case of pillar formation in termite nests (e.g. Franks and Deneubourg, 1997; Camazine et al., 2001). In this event, negative feedback takes over when there is no more material in the area close to the formation of these types of pillars. It has also been observed that there seems to be a certain type of competition among termites building other pillars in the same area. This pattern of competition is recognised as negative feedback.
Positive feedback coupled with negative feedback provides a powerful mechanism for creating and balancing structures and patterns in many physical and biological systems. Kauffman (1995) points out that feedback and its consequences also apply to organisations – driven by simple behavioural rules, actions and activities. Examples include attraction, aggregation, self-enhancement, clustering and amplification, and they lead to the processes of self-organisation within an organisational system.
Another characteristic of self-organisation is the reliance of organisational processes on multiple interaction and passing of information among individuals. In fact, as Fuchs (2003) points out, ‘… all self-organising systems are information-generating systems’ and thus, ‘… information is a relationship that exists as a relationship between specific organisational units of matter’. Systems use communication to process meaning and perform internal and external operations, but it appears that it is the search for information that triggers the emergence of internal order.
Kauffman (1993; 1995) asserts that the patterns of communication of information in biological systems are characterised by cues and signals. It is the same for human systems. As Mingers (1997) describes it, the communication of information does not necessarily have to be characterised by language; symbolic interaction via cues or signs alone can generate the information transfer between individuals in a system.
Vanderstraeten (2000) asserts that the identity of information is established in the communication process. But what is the purpose of information? Based on systems theory (e.g. Checkland, 1981) information can be considered as the objective relationship between the elements inside the system’s structure and the environment of the system. This basically means that the purpose of information is to establish the relationship of reflection between a system and its environment. This interaction causes structural changes, which result in order, to emerge in the system. It is important to highlight that a system’s environment also refers to the surrounding self-organised systems – or neighbours – from which information can be gathered.
Camazine, et al. (2001) assert that, in a good number of the cases, the most important information comes directly from an individual’s closest neighbours. So, it could be argued that information is a result of a cooperative process with an individual’s neighbours, from which coordination emerges. Fuchs (2003) points out that a detailed study of nature shows that cooperation within animal species and biological organisms is a main aspect of self-organisation. Human beings differ from animals in various ways but cooperation is, of course, also necessary for the existence of social systems. Even competitive situations that create negative feedback (e.g. competition among termites when building pillars) can still be considered cooperative processes that generate information (i.e. termites’ interaction) and cause a new order to emerge (i.e. new pillar constructions).
Fuchs (2003) asserts that, in a communication process, a portion of subjective, systemic information (cognition) is conveyed; hence cognition becomes the third aspect of information-generation in self-organising systems. He reiterates that ‘… information in self-organising systems has cognitive (subjective), communicative (new subjective information [= structures] emerges in systems due to interaction) and cooperative aspects (interaction results in synergies that cause the emergence of new, objectified information in the shared environment of the involved systems)’. These general aspects can be found in biological, physical and social self-organising systems. However, there are qualities unique to each of these systems and their correspondent environments.
The term ‘stigmergy’ was originally proposed in 1959 by the French scientist, Grasse, in his study of social insects, and more specifically, while observing termite building behaviour. Grasse’s stigmergy definition, as translated by Holland and Melhuish (1999, p. 2), indicates that:
‘… the coordination of tasks and the regulation of constructions does not depend directly on the workers, but on the constructions themselves. The worker does not direct his work, but is guided by it. It is to this special form of stimulation that we give the name Stigmergy (stigma, wound from a pointed object; ergon, work, product of labour = stimulating product of labor)’
This means that stigmergy describes the influence that information, derived from the local environmental effects of the activities of previous individuals, has on the current individuals’ behaviour.
Camazine, et al.(2001) refer to stigmergy as the process of information gathering from work in progress. In other words, working stimulus comes from the information gathered when individuals interact with environmental effects rather than from fellow workers. This is a further step in communication and cooperation among individuals of a system. As Camazine, et al.(2001, p. 24) describe it, in continuing with the social insect analogy:
‘… instead of coordination through direct communication among nestmates, each individual can adjust its building behaviour to fit with that of its nestmates through the medium of the work in progress’.
Stigmergy appears to be an important mechanism that assists a system to structure itself through the collective behaviour of individuals within the system’s environment. An individual could move through the environment, gathering or emitting information, but it can also interact with the environment. Both actions could be considered stigmergy.
Self-organisation is made possible by the coordination of activities that over time and space creates a pattern of construction. Stigmergy is effective in coordinating these construction activities and also in mediating interactions among workers through the environment. For that reason, it is an important component of self-organisation. However, it appears that stigmergy is not a complete explanation of such construction activities since there is no explanation of how construction ends, nor how errors made during construction are amended.
Stigmergy can explain the simpler aspects of transfer of information among individuals, where each individual needs to determine what to do and where a direct line of information from one individual to another individual does not exist; transfer instead occurs through the stimulus of previous individuals’ information and construction activities embedded in the environment. Figure 9.3, “Stigmergy – information flow.” summarises this process. Here the work previously accomplished by one or more individuals is imprinted in the environment as a cue and stimulus for other individuals. Thus individuals can interact socially by indirect transfer of information encountered in the environment through constructs made by others of their kind.
Camazine, et al. (2001) refer to decentralised control as another important concept underpinning self-organising systems. As with stigmergy, this concept addresses the flow of information within a system. In decentralised control mechanisms, the information gathered and shared by individuals does not follow a hierarchy of control. In fact, quite the opposite occurs; each individual gathers and acts on information independently. As a result, a natural coordination process of information shared and tasking among individuals takes place without relying on instructions from a leader. Each individual selects essential information for decision-making. This information often originates from the interaction among individual members of the system. This decentralisation of information flow provides the basis for multiple interactions among the components of a self-organised system, making these systems dynamic.
The dynamics of the system (i.e. the interactions, cues and stimuli among individuals, and the environment) are a clear indication of the relationship between stigmergy, decentralised control and self-organisation. As Camazine, et al. (2001, p. 61) point out:
In a decentralised system, each individual gathers information on its own and decides for itself what to do. Stigmergy is one means of information flow within a decentralised system that involves gathering information from the shared environment … These decentralised paths of information flow provide essential means of interaction among the components in a self-organising system.
Moreover, the multiple interactions are in themselves dynamic processes of pattern formation that constitute self-organising systems.