Complex system

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Complex systems are systems (totalities of objects that are in a holistic context and are to be delimited from their surroundings by the interrelationships between them), which refuse to simplify and remain complex. In particular, this includes the complex adaptive systems that are able to adapt to their environment.

Their analysis is a matter of complexity theory (English complexity theory ) or systems theory , which is to be distinguished from complexity theory in the IT sense. The scientific description or investigation of complex systems is collectively referred to as complexity research .

In addition, analyzes and measures the combinatorial game theory , the game complexity with the following metrics:

  • State space complexity
  • Game tree size
  • Decision Complexity
  • Game tree complexity
  • Computing effort

Complex systems are the object of complexity reduction and complexity management .

properties

Complex systems show a number of properties (selection):

  1. Agent-based : Complex systems consist of individual parts that interact with one another (molecules, individuals, software agents, etc.).
  2. Nonlinearity : Small system disturbances or minimal differences in the initial conditions often lead to very different results ( butterfly effect , phase transitions ). The interrelationships of the system components are generally non-linear .
  3. Emergence : In contrast to merely complicated systems, complex systems show emergence . Contrary to a common simplification, emergence does not mean that the properties of the emerging system levels are completely independent of the levels below. However, emerging properties cannot be explained from the isolated analysis of the behavior of individual system components and can only be derived to a very limited extent.
  4. Interaction ( interaction ) : The interactions between the parts of the system (system components) are local, their effects are usually global.
  5. Open system : Complex systems are usually open systems . So they are in contact with their environment and are far from thermodynamic equilibrium . This means that they depend on a permanent flow of energy or matter.
  6. Self-organization : This enables the formation of generally stable structures (self-stabilization or homeostasis ), which in turn maintain the thermodynamic imbalance. You are able to process and learn information.
  7. Self-regulation : This allows you todevelopthe ability for internal harmonization . You are therefore ableto strengthenyour inner equilibrium and balance on thebasis of the information and its processing.
  8. Paths : Complex systems show path dependency : their behavior over time is not only dependent on the current state, but also on the previous history of the system.
  9. Attractors : Most complex systems have so-called attractors , which means that the system strives for certain states or sequences of states independently of its initial conditions, whereby these sequences of states can also be chaotic; these are the "strange attractors" of chaos research .

example

The human brain is an example of a complex system, as it is made up of multiple interlinked building blocks, the neurons, and other accompanying cells whose function is largely unknown. Consciousness is possibly an emergent phenomenon in the human brain. However, a distinction must be made here between consciousness itself (as a medium in the ontological sense) and consciousness content as information that manifests itself within the ontological medium 'consciousness'. Further, v. a. (Highly) complex systems known from everyday life are e.g. B. the Internet, financial markets, multinational corporations, but also the human nervous system, humans themselves, infrastructure networks and the like.

Well-known researchers

Important institutes for research into complex systems

Institutions in Germany

Institutions in Austria

literature

Web links