Characterizing Systems

• ¹ A system is an interconnected set of elements that is coherently organized in a structure, and which produces a characteristic set of behaviors.
• We can define the system more formally. A system where
  • is the index related to the level of complexity,.
    • The system of interest having is at the top.
    • When is decomposed and each is treated as its own system, , we have a new system with level of complexity
  • is a multiset of of component subsystems where
    • is the type and may be a subsystem at lower complexity (at level ).
    • is an integer enumeration of the number of components of the particular type.
    • The number of times a tuple appears is equal to the number of variations of that tuple
  • is a network description of the system, in particular which internal components are connected and at what level of complexity.
  • is a bipartite graph where half of the nodes are entities in the environment, the other half are component subsystems .Edges indicate the connections between objects in the environment and objects in the subsystem
  • is a complex object that describes the boundaries of the system.
  • is a complex object that describes the dynamics — that is, how the components interact with each other and the environment.
  • is a complex object of the history of the system or its state transitions as it develops.

Principles of Systems §

Systemness §

• Systems are bounded objects that can be delineated from the environment with boundaries. Such boundaries are either real or arbitrarily set.

• Systems can be nested — containing smaller subsystems. The whole contains parts and yet the whole is also more than the sum of its parts

• Changing a system’s elements, interconnections or purposes changes its behavior.

• As new levels of complex organization emerge, the new levels intertwine in dynamic systemic relationships with other levels. In particular we can consider four levels

  • Ontological - systems in the world / observable universe. It is primarily concerned with parts and wholes. This is what the Natural Sciences study.
  • Epistemological - systems in the mind or relating to knowledge and information as perceived by an observer. These are formed in the brain. This is studied by the Social Sciences.
  • Abstract - Mathematics or symbolic language aspect. The abstract is either made concrete either through concrete measurements (i.e., in the Sciences) or through Natural language.
  • Software - Systems in Software

Domains in Systems. Image taken from Mobus and Kalton

• See more here

Processes §

• *Systems are Processes Organized in Structural and Functional Units
• The least obvious part of the system, its function or purpose, is often the most crucial determinant of the system’s behavior, and it can only be deduced by examining this behavior.
• System structure is the source of system behavior. System behavior reveals itself as a series of events over time. The structure comes from interrelated stocks, flows, and feedback loops.
• See more here

Networks §

• Systems are networks of relations among components and can be represented abstractly as such network of relations.
• Many of the interconnections in systems operate through the flow of information (via decisions or actions) or resources. These serve to hold the system together and determines how it operates.
• See more here.

Dynamics §

• Systems are dynamic over multiple spatial and time scales.
• Systems constantly adjust themselves by feedback loops , but when interdependent components operate with feedback loops of different temporal scales, the system may become unstable
• In general for the dynamics of the system, the lower the resolution in spatial dimensions, the lower the resolution in the temporal dimensions.
• See more here.

Complexity §

• Systems exhibit various kinds and levels of complexity.
• The purpose of a system may be emergent and even accidental — as in no actor intends for such to happen but the structure of the system makes it so.
• Complexity and nonlinearity can, themselves, be sources of disruption or failure.
• See more here.

Evolution §

• Systems evolve. Either towards higher organizations, maintaining a steady-state, or decaying.
• The evolution of systems is based on its flows. When inflows are too low, entropy takes over and the system deteriorates towards disorder

Information §

• Systems encode knowledge and receive and send information.
• The system, by its very own structure, knows how to react to a situation.

Regulation §

• Systems have regulatory subsystems to achieve stability.
• As systems evolve toward greater complexity, the interactions between different levels of subsystems require coordination and control in the form of feedback loops

Models of Others §

• Systems can contain models of other systems.
• Systems and subsystems can expect certain forms of systemic relations to be present. In general, systems encode in some form models of the environment or aspects of the environment with which they interact
• See more here.

Models of Themselves §

• Sufficiently Complex, Adaptive Systems Can Contain Models of Themselves
• Adaptive systems can modify their models of an environment and of themselves to better adapt to the dynamics of the environment
• See more here.

Understandability §

• Systems can be understood
• In principle systems function in terms of relational dynamics , and this is an appropriate object for human understanding.
• Systems afford predictability by constructing and testing models.
• Even though systems are black boxes, we can study their functions and develop models about the internals of the system.
• Modeling is made more complicated by the fact that observers are typically part of the system they are observing. Thus, the observers themselves can change the system and the observations they make are not necessarily objective truths about the system (see observer bias).
• See more here.

Improvability §

• Systems can be improved.
• A systems-oriented account of evolution will have to take up the question of when and how causal functioning gets to the condition where the operation of the system can be observed to aim selectively at some kind of result. That is, there is a metric of interest that is improved over time as a result of evolutionary processes.

Links §

• System Dynamics
• Thinking in Systems by Meadows - Ch. 1
• Principles of Systems Science by Mobus and Kalton - Ch. 1 - 3

Footnotes §

1. Properties are from Mobus and Kalton - Ch. 1.4 ↩