Organism, brain, society, language...
A system not merely constituted by the sum of its components, but also by the intricate relationships between them. Complex systems cannot be divided up into logical pieces and understood analytically in the traditional manner; you thus end up destroying what you seek to understand. Rather, they must be taken in their entirety and approached holistically through powerful modelling techniques, using technology to take us where currently science cannot.
To truly understand what a complex system is, it is crucial that one understands the distinction between a complex and a merely complicated system for they are easily confused. Some systems contain an extremely large number of components and are quite sophisticated in their operation, yet they can be analyzed accurately and modelled exactly (sound familiar? You're sitting in front of one right now*). These systems are only complicated. Other systems consist of nonlinear relationships, intricately linked feedback loops, and recursive behaviour, where only certain aspects can be analyzed at any given time. These systems are complex.
South African philosophy professor and former research engineer Paul Cilliers offers a list of the 10 fundamental characteristics of complex systems in his 1998 book, Complexity and Postmodernism:
- Complex systems consist of a large number of elements
- The elements in a complex system interact dynamically (changing with time, constantly transferring information)
- The level of interaction is fairly rich (any element in the system influences and is influcenced by quite a few others)
- Interactions are nonlinear
- The interactions have a fairly short range (wide-ranging influence is still possible, but elements interact locally)
- There are loops in the interconnections (any activity can feed back onto itself)
- Complex systems are open systems (they interact with their environment)
- Complex systems operate under conditions far from equilibrium (there has to be a constant flow of energy to ensure survival; equilibrium = death)
- Complex systems have histories (memory)
- Individual elements are ignorant of the behaviour of the whole system in which they are embedded (a distributed system)
*Though it should be noted that as computers rapidly become more capable (in terms of hardware and software), the ability to model them accurately will diminish, pushing them into the realm of true complexity. It can probably even be argued that they're already at that point now, so perhaps a better example would be something like a DVD player or an industrial robot.
REFERENCES:
Cilliers, Paul. Complexity and Postmodernism: Understanding Complex Systems. London: Routledge, 1998.
| 
