Structures (actors, components, animals or machines) perform behaviors.
Understanding the structural roles played by actors is part of understanding a system.

The individual actors may come and go; and understanding individual animals or machines is different from understanding a system they play a role in.

This table distinguishes structures and behaviors.

Structures in space	Behaviors over time
Actors (active structures) who perform activities. Passive structures that are shaped or directed by behaviors. Entities that are created, changed and destroyed by events. Stocks that are incremented and decremented by flows. Components that respond to service requests and perform processes.	Activities in processes performed by actors Behaviors that are performed by active structures. Events that create, change and destroy entities. Flows that increment and decrement stocks. Services delivered and processes performed by components.
Along the lines defined in UML	Along the lines defined in UML
A passive object, or an active actor with a thread of control. Actors respond to messages generated by actors that perform communication actions. All behavior is triggered by and composed of actions performed by actors. An actor instantiates an entity type/role by performing the behaviors of that type/role.	Actions, and sequences of actions in longer behaviors. An action converts a set of inputs and into a set of outputs. Repeatable behaviors are often modelled as discrete event-driven processes. The time between events can small enough to simulate continuous behaviors

Natural and designed systems

A natural system has evolved without any intent, though some may speak of its accidental outcomes as its aims.

A designed system was created by intent; so, it can be tested by comparing its outcomes with its aims.

If it ain’t described before it exists, then ain’t designed.

Abstract and concrete systems

Ashby was keen we separate abstract system descriptions from physical entities that realise them.

This triangle represents the idea more graphically.

System theory

Abstract systems

Systems thinkers <observe and envisage> Concrete systems

We can model the state of the solar system in terms of variables whose values can be measured (e.g. the positions of the planets).

And model whatever regular processes can change the values of those variables (e.g. the orbits of the planets).

And then test that the real planets behave according to the description in our model.

Every real tennis match is unique in the immensely rich and complex detail of individual player’s actions.

Every tennis match is the same in so far as it conforms to the abstract description of a tennis match’s qualities in the laws of tennis.

Suppose a tennis player scratches his nose; that is an act in reality but not in the tennis match system.

The action is irrelevant to the target system controlled by the umpire.

The player’s breathing and biochemistry (though essential in reality) are also outside the described system.

Note that the actors playing roles in one concrete system can play roles in other systems at the same time.

For example, orchestra members are more than the parts they play in a symphony performance; they simultaneously play roles in other systems.

They are tax payers in a tax system - sons or daughters in a family – guests in a hotel system.

These disparate systems do not meaningfully add up to one system, unless and until the systems are related in one holistic system description.

Systems

The term system is overloaded with different meanings.

It can refer to:

· a passive structure of connected things and/or an abstract system description.

· a concrete system, composed of actors interacting in roles according to the rules that characterise the system.

· a abstract system, composed of actors interacting in roles according to the rules that characterise the system.

Passive structure: an element or group of related elements that may be acted on, but does not act.

E.g. the Dewey decimal system, the Linnaean classification system, a telephone directory, or a data structure.

Activity system: an island of orderly behavior.

A structure of elements that interact (directly or indirectly) in regular or repeatable behaviors.

The behaviors may maintain or advance the state of the system, consume inputs or deliver outputs.

E.g. the solar system, an organism, a software system, a choir, a tennis match.

Abstract system: a description or model of a concrete system.

E.g. a physical model, a narrative, a context diagram, a network diagram, a causal loop diagram, or a combination of such artifacts.

Abstract descriptions do take concrete forms (they are found in mental and documented models).

At the same time, they describe (model, conceptualise, idealise) a physical reality that can be envisaged or observed as matching the description.

Concrete system: a system that runs in reality.

A realization in physical matter and/or energy of an abstract system description.

The realisation by a real world entity of an abstract system – near enough to satisfy the observer.

One concrete entity can realise many different abstract systems.

So, to say an entity is "a system” implies a particular description of the behaviors that characterise it.

Wholes and parts

Holistic view: a description of how parts relate, interact or cooperate in a whole.

E.g. a description of how the muscles of the human heart interact.

Emergent property: a behavior or structure of a whole that depends on interactions between its parts.

Atomic element: a part that is not further divided in a description of a system.

Atomic system actors may be complex entities in their own right, and may play roles in other systems.

Reductionist view: identifying the parts of a whole, naming or describing parts without considering how the parts are related in the whole.

Read our paper on Holism and emergent properties for more.

Organicism: the idea that systems are describable at multiple hierarchical levels.

System of systems: a nest, combination or container of systems that are separately described.

System boundary

“Every living organism is essentially an open system. It maintains itself in a continuous inflow and outflow…” Bertalanffy

System environment: the world outside the system of interest.

Most system design methods separate a system from its wider environment

The environment of one system may be a wider system.

Closed system: a system that does not interact with anything in the wider environment.

All events of interest are internal to the system.

E.g. A System Dynamics model is a closed system of stocks and flows.

Open system: a system that interacts with entities and events in a wider environment.

Inputs can change the state of the system; outputs can change the state of entities in the environment.

Many system design methods scope a system by its inputs and outputs

System boundary: a line (physical or logical) that separates a system from is environment

It encapsulates the system’s internal structures and behaviors.

It defines the system’s input-process-output boundary.

Inputs and outputs can be flows of material, energy or information.

System interface: a description of inputs and outputs that cross the system boundary.

An interface defines the system as it is seen by external observers.

An interface may be defined in a contract defining services provided or required.

In social and software systems, the primary inputs and outputs are information flows.

Read our paper on System boundary for more.

Interactions between system actors

“connected with system theory is… communication. The general notion in communication theory is that of information.” Bertalanffy

Interaction: an exchange of forces, materials or energy or information.

It is usually presumed that all actors in an activity system interact (directly or indirectly) else there would be two or more separate systems.

Information: a meaning created or found by an actor in any physical form that acts as a signal.

Any description or direction that has been encoded in a signal or decoded from it by an actor.

Signal: any structure of matter or energy flow in which an actor creates or finds information.

In human communications, the physical forms include brain waves and sound waves.

In digital information systems, the physical form is a data structure in a binary code.

Information flow (aka message): physically, a signal passed from sender to receiver, logically, a communication.

Information state (aka memory): see “state”.

Information quality: an attribute of information flow or state, such as speed, throughput, availability, security, monetary value.

“A second central concept of the theory of communication and control is that of feedback.” Bertalanffy

Information feedback loop: the circular fashion in which system inputs influence future outputs and vice-versa.

Brains and businesses can both be seen as information systems.

Both maintain a monitor-direct feedback loop with their environment:

· They detect events and changes in their environment - via input information flows.

· They remember the entities and events they monitor - in an internal model or information state.

· They send messages to direct those entities and events.

If the system does not monitor and direct entities and events in its environment – well enough - then it expires or is changed.

Read our papers on Communication theory and Information feedback loops for more.

Somewhat related concepts include the following.

Entropy: disorder; across the universe, the total entropy increases with time.

Chaos: unpredictable disorder in how things relate to each other or change over time.

Autopoesis: the process by which organisms build and maintain their bodies from primitive chemicals consumed.

System structure and behavior

“Systems concepts include: system-environment boundary, input, output, process, state….” Principia Cybernetica

State: the current structure of a thing, as described in the current values of its variable properties.

An entity’s concrete state is directly observable in the values of its physical position, energy and material variables.

E.g. the location, temperature, colour, and matter state (solid/liquid/gas) of a thing you see in front of you.

Information state is found in the values of descriptive variables held in a memory or database of some kind.

(Homeostatic behaviors (maintaining a system’s state variables in a desirable range) may run cyclically or continually.

By contrast, end-to-end behaviors run from start to end, yielding a result or output.

In business systems, these behaviors are usually called value streams, scenarios or processes.

The trigger that starts an activity (or sometimes the activity itself) is often called an event.)

Event: a discrete input that triggers a process that changes a system’s state, depending on the current state.

(Note: this is the basis of modelling a system using discrete event dynamics and System Dynamics.)

(Note: information systems also consume enquiry events that report current state.)

Process: one or more state changes over time, or the logic that determines which state changes lead to which other state changes.

In the abstract, description or specification of how state changes over time, either in discrete steps or continuously.

E.g. a flow chart showing the control logic governing event-triggered activities that result in discrete state changes.

E.g. mathematics describing the continuous change to the position of a planet in its orbit.

A concrete process may be directly observed in changes to the state of the world.

E.g. an apple falls from a tree; a cash payment is handed by one actor to another.

Hysteresis: the process by which a system’s information state can be derived by replaying all events that have so far crossed the system boundary.

Read our paper on Determinism and hysteresis for more.

System stability and change

“Cybernetics deals with all forms of behavior in so far as they are regular, or determinate, or reproducible.” Ashby 1956

In Ashby’s view (as many dictionary definitions suggest) a system is orderly rather than disorderly.

He wrote that the notion of a deterministic system was already more than century old.

Deterministic: the quality of a system that means its next state is predictable from its current state and input event.

A deterministic system, in a given state, will respond to a specific stimulus or event by acting in a predictable way.

Paradoxically, as a result of processing a series of events, a system may change in an unpredictable, chaotic or non-linear fashion.

Read our paper on Determinism and hysteresis for more.

Again, a system is an entity whose behavior is organised, regular or repeatable.

Like every other discrete entity, such an activity system has a discrete life time, which can be long or short.

System	Life span	Actors/Roles	Activities/Rules
In our solar system	for eons	the planets	orbit around the sun, as determined by the law of gravity.
In a human body	for years	the organs	process chemicals, as determined by instructions encoded in DNA.
In a clock	for days	the pendulum	sways back and forth, converting a coiled spring's energy into clock hand movements.
In a tennis match	for hours	the players	behave in an orderly way, as determined by the laws of tennis.
In a symphony performance	for minutes	the orchestra members	make sounds, as scripted in a musical score.

Ashby was keen we differentiate inter-generational system mutation from system state change within the life span of a system.

“The distinction is fundamental and must on no account be slighted.” Ashby (1956)

System state change: a change to the state of a system, which changes the value of at least one variable.

Discrete (or digital) state change: a system’s state advances incrementally in response to discrete events.

Continuous (or analogue) state change: a system’s state advances continually in response to continuous forces or inputs

Linear change: progress or change over time that is represented in a graph as a straight line (or else a regular shape).

Non-linear change: progress or change over time that is represented in a graph as a curve (or else an irregular shape).

System mutation: a change to the nature of a system, which changes the type of at least one variable or behavior.

The following three notions are central to modelling activity systems.

1) The state of an activity system may change.

2) The roles and rules of a system are fixed for a system generation.

3) Changing the roles or rules makes a new system version, or a different system.

Meta system: a system that defines a system or transforms it from one generation to the next.

Read our paper on System stability and change for more.

Natural systems and designed systems

A natural system has evolved without any intent, though some may speak of its accidental outcomes as its aims.

A designed system was created by intent; so, it can be tested by comparing its outcomes with its aims.

If it ain’t described before it exists, then ain’t designed.

Generic concept	Natural systems		Designed systems
	Cosmology	Biology	Business	Software
Actors	Planets are	Cells	Humans and machines	Objects
Roles	bodies in space that	play roles in	play roles in	instantiate classes so as to
Behaviors	complete orbits and	performing processes and	performing processes and	transform and remember data and
Interactions	exchange forces that	exchanging materials that	exchanging information to	exchange information to
Outcomes	maintain the solar system.	sustain an organism.	meet business goals	monitor and direct external entities

Natural system: an entity that behaves as a system before it is perceived to be a system.

Its repeated behaviors are the outcome of evolution rather than the ideas of a living entity.

E.g. The solar system behaved as a system before it was described.

Other examples: a weather system, biological organism, the Krebs cycle.

The correspondence of the real solar system to its description need not be perfect.

It only needs to be near enough to help people predict its behavior – well enough.

Designed system: an entity that behaves as a system only after it has been conceived by a living entity.

Its reproducible behaviors are a response to the interests or aims of one or more living entities.

E.g. A professional tennis match is conceived and described in the laws of tennis.

Other examples: a cuckoo clock, a motor car, an accounting system, a choir, a tennis match, the world cup.

The correspondence of the phenomena in a real tennis match to its description need not be perfect.

It only needs to be near enough to help people predict and direct its behavior – well enough.

Social networks, systems and cells

Social network: a group of actors who may chose their own behaviors, and may interact to reach agreed aims.

E.g. the group of actors hired to play in an orchestra, who may agree to hold a party after the performance.

Since the roles and rules of a social entity are adhoc and in flux, it cannot be described and tested as matching that description.

Social system: a social entity in which animate actors play roles in regular, repeatable processes.

E.g. bees collecting pollen for a beehive; an orchestra’s performance of a symphony.

The symphony score is a system description; every performance of that symphony instantiates that system description in reality.

System theory is primarily about the roles in the symphony (the system).

Some systems thinking is more about the social entity - the actors in the orchestra, and their motivations.

A social entity may succeed in meeting goals, of its actors or sponsors, despite the roles and rules of a system in which the actors work.

But the ideal business is a social entity in which actors work happily in the roles of whatever system those actors are hired to work in.

Social cell: a social system whose roles reward the actors of a social entity sufficiently well to ensure the actors voluntarily perpetuate the system.

In other words, there is a symbiotic relationship between the roles of the social system and the actors of the social entity.

E.g. regular choir rehearsal meetings, a tennis club, and Japanese tea ceremonies.

Reward examples include hope, comfort, endorphins and money.

The very idea of a particular social cell may be so appealing that other actors, who hear of it, may replicate it (cf. Dawkin’s “meme”)

Read our paper on Social cells for discussion of a social cell as mutually beneficial, or insidious, or even as a parasite on society.

Business terms

Enterprise: has several meanings; usually implies a business led by executive managers/directors, or a segment thereof.

Organization: generally, a structure in which elements are related; here, a structure in which human roles of enterprise are related; it usually implies lines of command and control.

Management system: generally, a system that monitors and directs an entity; here, one that monitors and directs the operational systems of an enterprise.

Team: generally, a group of actors who interact; sometimes a node in an organisation structure; sometimes a group dedicated to the completion of a behavior (a project or task).

Description theory terms

Thing: a subdivision of the universe, locatable in space and time, describable as instantiating one or more types.

Natural thing: a thing that emerges from the evolution of matter and energy, regardless of description.

Organism: a natural thing whose form is defined by it genes, and engages in the process of Darwinian evolution.

Designed thing: a thing described by an organism before it is created.

Describer: a thing (organism or machine) that can create and use a description.

The survival of describers depends on their ability to create and use descriptions of reality.

Description: a thing that idealises another thing by recording or expressing some of its properties.

A memory, message, model or view that captures/encodes knowledge of a thing’s properties.

It enables that knowledge to remembered and/or communicated.

It enables some questions about the described thing to be answered.

Set: a collection of things that are similar in so far as they instantiate (embody, exemplify) one type.

Type: an intensional definition, composed of property type(s) that describe a thing.

Instance: an embodiment by one thing of a type, giving values to the properties of that type.

Sign: a name, image or effect of a thing or a type, which describers use in recognising, thinking or communicating about that thing or type.

Token: an appearance of a sign or a type in a memory or message.

Read our paper on Introducing Description Theory for more.

Questionable concepts and principles

Today’s general system theorist need not embrace all Bertalanffy wrote.

Some ideas von Bertalanffy supposed to be general don’t appear in this update of GST.

Hierarchy?

Read our paper on Hierarchical and network organisations for discussion.

Inexorable progress?

Read our paper on Marxism, system theory and EA for discussion.

Goal directedness?

Read our paper on Goal-directedness for discussion.

Complex?

The term implies complicated in some way, but there no agreed measure of complexity.

So, a complex entity may realise a simple system.

Every hamburger is infinitely complex; but the recipe for a hamburger is a relatively simple abstract system description.

Every real-world US government is infinitely complex; but the US constitution is relatively simple abstract system description.

A US government can be called a system where and in so far as it realises the US constitution.

But most of the time, government actors are choosing and performing activities in ad hoc ways not explicitly described in the constitution.

As a social entity, the US government is infinitely complex; as a system it is relatively simple.

Read our paper on Complexity for more.

In systems thinking discussions, the following pairs of terms are often confused; but strictly, each pair represents two distinct concepts.

Holistic versus Systemic

Holistic: considering how the parts of a whole are related; taking a view that addresses how parts cooperate to the benefit of the whole.

Systemic: relating to the whole rather than a part; reaching throughout the whole, pervasive throughout a system.

(E.g. A systemic drug or disease that reaches and has an effect on the whole of a body.)

To be holistic isn’t the same as being pervasive throughout a system.

Reductionism versus Analysis

Reductionist view: identifying the parts of a whole, naming or describing parts, without considering how the parts are related in the whole.

Analysis: dividing a whole into parts, which can at the same time reveal how the parts are related in the whole.

Analytic(al) versus Systematic

Analytic (aka analytical): using or skilled in using analysis; separating a whole (description or reality) into parts or basic principles.

Systematic: methodical, acting according to a fixed process or system.

You may be analytical in a systematic way; but you may be systematic without analysing anything.

Conclusions and remarks

This paper has attempted to restore order to the concept of a system - along the lines defined by Ashby.

Systems are islands of orderly behavior, describable in terms of roles for actors and rules for activities.

Actors are structures or components that exist in space and perform activities expected of their roles.

Activities are behaviors that happen over time, and change the state of the system or something in its environment.

An abstract or theoretical system is a description of roles played by actors, and rules governing their activities.

The scope of the system is determined by its describers.

Give some aims or interests, describers focus on some activities performed by some actors

They describe instances of actors and activities as general types - the roles and rules of the system.

A concrete or empirical system is an entity in which actors play roles in performing described activities.

An entity is only an empirical system when, verified by observation, its behavior matches that of a theoretical system.

Ashby's idea of a system gives us insights into a wide variety of disciplines.

Together with Darwin's theory of evolution, it leads us towards theories of information and communication.

It leads us towards answers to philosophical questions about description and reality.

And helps us to make sense of what enterprise architecture is about.

Footnote on behaviors

A concrete process may be directly observed in changes to the state of the world.

E.g. an apple falls from a tree; a cash payment is handed by one actor to another.

An abstract process is a description or specification of discrete or continuous state change.

E.g. a flow chart showing the control logic governing event-triggered activities that result in discrete state changes.

E.g. mathematics describing the continuous change to the position of a planet in its orbit.

The universe may be viewed as ever-unfolding processes.

And the structures within it viewed as results of those processes.

E.g. Stars and planets can be seen as side effects of gravitational forces.

A biological entity maintains itself cyclically by what is called autopoiesis.

The processes are performed by structural elements.

The structural elements are manufactured and maintained by processes.

A designed activity system may be viewed as a set of designed processes.

And some structures within it may be manufactured by those processes.

However, we must hire or build active structures (actors/components) to perform designed processes.

E.g. hire musicians to perform the parts in a symphony.

It is wrong to think of people (hired to play roles) as parts of a designed system.

The parts are performances of system roles by people.

The people live outside of any system they play a role in, and are much more than any role they play.

In practical systems analysis and design it is normal to distinguish processes from systems.

A system has persistent structure (describable in a network or data flow diagram) in which actors perform processes in parallel.

A process is an event-triggered behaviour (describable in simple flow chart) that runs from start to end over time.

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