Introducing System Theory and Cybernetics

Copyright 2016 Graham Berrisford.

One of about 300 papers at http://avancier.website. Last updated 29/03/2017 22:48

 

An architecture defines a system” TOGAF 9.1

“Enterprise architecture structures the business planning [and] regards the enterprise as a system or system of systems.” TOGAF 9.1

OK, but what is a system?

The principles of general system theory (GST) are applied all over the world, every day, to the description and design of successful systems.

They can be applied to things as diverse as tennis matches, brains, businesses and software.

This is only an introductory paper; there is a great deal more to learn.

Contents

General system theory (after von Bertalanffy) 1

Generalising from other sources. 4

Abstraction and cybernetics (Ashby) 6

Cybernetics (Weiner) 7

Soft systems (Checkland) 9

Discrete v continuous system dynamics (Forrester) 9

Other ideas and developments. 11

Footnotes. 11

 

General system theory (after von Bertalanffy)

Ludwig von Bertalanffy (1901-1972) is regarded as the founder of General Systems Theory (GST).

In 1954, Bertalanffy and others (including Boulding) establish Society for the Advancement of General Systems Theory.

In 1968, Bertalanffy published General System theory: Foundations, Development, Applications.

“There exist models, principles, and laws that apply to generalized systems or their subclasses, irrespective of their particular kind, the nature of their component elements.” Bertalanffy

 

Consider for example, systems described by sociologists, biologists, psychologists and control system engineers:

·         Sociology: people communicate in response to messages, in the light of their memories (or “mental images” as Boulding called them in 1956).

·         Biology: cells respond to chemical/electrical signals, in the light of their current chemical state.

·         Machine regulators: components send messages to devices in response to messages received about environment state changes.

·         Computing: objects perform operations in response to messages, in the light of current state variable values.

·         Entity/event models: entities change state in response to events, in the light of current state variable values.

·         System dynamics: stocks change volume in response to event flows, in the light of current stock volumes.

 

Today’s general system theorist need not embrace all Bertalanffy wrote.
He considered a biological entity as a thermodynamic system.

“By importing complex molecules high in free energy, an organism can maintain its state, avoid increasing entropy...

OK, except that decay and death are an essential feature of life.
"and even develop towards states of increased order and organization."

This seems to confuse the life of an organism, the “progress” of biological evolution, and perhaps the “progress” of human history.


In the following decades, he stretched this idea into proposals about human psychology and the meaning of life.

“Life is not comfortable setting down in pre-ordained grooves of being; at its best, it is élan vital, inexorably driven towards higher forms of existence”.
Yet the best evolution can do might be sharks, that are believed to have remained much the same for 100 million years.

And of all species that have existed on Earth, 99.9 percent are now extinct.

And many biologists believe we are currently in the throes of a sixth mass extinction.

 

Bertalanffy’s views of life, evolution, and the human condition are questionable.

But the six core ideas that follow are more widely accepted, and are reflected in modern Enterprise Architecture methods like TOGAF.

 

Holism or wholeness

Bertalanffy wanted to shift attention from the parts of a system to the whole.

“General System Theory… is a general science of wholeness… systems [are] not understandable by investigation of their respective parts in isolation.” Bertalanffy

 

Note that to take a holistic view of a system implies you are aware also that it is divided into parts.

Holistic and reductionist views of system are complementary, not antagonistic.

EA takes a holistic view of a business, TOGAF “regards the enterprise as a system of systems”.

 

The primacy of behavior

Bertalanffy wanted to shift attention from static parts to how they are related in dynamic behavior, to “phenomena not resolvable into local events.”

Others have considered this to be the fundamental innovation of system theory.

TOGAF starts not from the structure of a system but from the services required of it.

And is concerned with the end-to-end processes (value streams, scenarios) needed to provide those services

 

The concern of GST is activity systems that operate in the real world, displaying regular, repeated or repeatable behaviors.

“A set of elements or parts that is coherently organized and interconnected in a pattern or structure that produces a characteristic set of behaviors." Meadows

 “The principal heuristic innovation of the systems approach is what may be called ‘reduction to dynamics’ as contrasted with ‘reduction to components’ ” Laszlo and Krippner.

"Cybernetics does not ask "what is this thing?" but ''what does it do?" It is thus essentially functional and behavioristic.”

“[It] deals with all forms of behavior in so far as they are regular, or determinate, or reproducible.” Introduction to Cybernetics (1956) W. Ross Ashby)

Read “The primacy of behavior” for more.

 

Recursive system description

Bertalanffy promoted the idea of "organicism," that systems should be treated (like organisms) as describable at multiple hierarchical levels.

·         A description of a human society likely ignores the innards of a human body.

·         A description of a human body likely ignores the innards of a human cell.

·         A description of a human cell likely ignores the innards of a molecule.

 

It is well-nigh axiomatic that:

·         Systems can be hierarchically nested: one system can be a part or subsystem of another.

·         An event that is external to a smaller system is internal to a wider system (and vice-versa).

·         The emergent properties of a small system are ordinary properties of any wider system it is a part of.

TOGAF recursively decomposes business functions/capabilities and processes.

 

System-environment boundary

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

TOGAF regards a business as a system that maintains itself in a continuous inflow from suppliers and outflow to customers.

 

Information flows

In the social, business and software systems of interest to us, the primary inputs and outputs are information or data flows.

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

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

TOGAF defines information flow feedback loops between businesses, customers, suppliers and employees, in terms of services requested and provided.

 

System state

A system has an internal state, which changes over time.

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

TOGAF defines data stores that hold data entities, which record the state of business entities and activities.

 

Any brain or business can be seen as a control system connected in a feedback loop with its environment.

It receives information about the state of entities and activities in its environment.

It records that state information in memory.

It outputs information to inform and direct motors, actors and entities as need be.

The state information must model reality well enough, else the system will fail.

Generalising from other sources

This table defines three core concepts in system description.

Terms

Example

Meaning

Aims

win the world cup

target outcomes that give an entity a reason or logic to perform and choose between actions.

Behaviors

compete in world cup matches

processes than run over time with intermediate outcomes and a final aim or ideal.

Active structures

players in a national football team

nodes, related in a hierarchy or network, that perform activities in behaviors.

 

Principle: The primacy of behavior

GST is concerned with activity systems that operate in the real world, displaying behavior of some kind.

“A set of elements or parts that is coherently organized and interconnected in a pattern or structure that produces a characteristic set of behaviors." Meadows

The systems can be characterised as having parts that interact in “regular, repeated or repeatable behaviors” W Ross Ashby.

 

A system is an entity whose processes act to maintain the state of the system and/or reach another goal.

This table compares a generalised description of a system (distilled from analysis of many different sources) with two sources not used in that analysis.

General System Theory

In EA/TOGAF terms

In Donella Meadows’s terms

A bounded structure of

A bounded organisation of

A bounded and coherent organization/structure of

actors/organs that interact by playing

actors/components that interact by playing

elements/parts that interconnect dynamically by performing

roles in

roles in

*

behaviors to meet

processes to meet

behaviors to meet

goals, by maintaining

goals/objectives/requirements by maintaining

functions/purposes by exchanging

system state and exchanging

data entities and providing

*

inputs/outputs with each other and with

input/output services to each other and to

inputs/outputs with each other and with

entities outside the boundary, using

entities outside the boundary, using

entities outside the boundary.

system resources.

platform technology components.

*

 

* System Dynamics advocate Meadows doesn’t mention roles, system state or resources in the quotes below.

 “System: A set of elements or parts that is coherently organized and interconnected in a pattern or structure that produces a characteristic set of behaviors, often classified as its function or purpose."
"Every system must exhibit these 8 characteristics in order to qualify as a system: Boundaries, Elements/Parts, Coherent Organization/Structure, Interconnections, Function or Purpose, Behavior greater than sum of parts, Inputs/Outputs, is Dynamic."

 

Principle: concrete systems realise abstract ones

A system is a set of elements that relate or interact in a structured or orderly way.

All the elements must be related directly or indirectly, else there would be two or more systems.

This definition embraces both passive structures (e.g. tables) and activity systems.

The concern of GST is activity systems, in which structural elements interact in orderly behaviors.

 

There are two forms of system: a concrete system realises (or instantiates) an abstract system description (or type).

Abstract system description

Theoretical system

System description

Concrete system realisation

An empirical system

A system in operation

 

An abstract system is a system in which the elements are concepts.

It may be purely conceptual, or describe an imagined or envisaged reality, or describe an observed reality.

Abstract system description

The Dewey Decimal System

“Solar system”

Laws of tennis

Defined roles (e.g. Orchestral parts)

The score of a symphony

 

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

Whatever form they take, they may describe (model, conceptualise, idealise) a physical reality that is it observed or envisaged.

 

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

There are two forms of system: a concrete system realises (or instantiates) an abstract system description (or type).

Abstract system description

The Dewey Decimal System

“Solar system”

Laws of tennis

Defined roles (e.g. Orchestral parts)

The score of a symphony

Concrete system realisation

Books sorted on library shelves

Planets in orbits

A tennis match

Actors (e.g. Orchestra members)

A performance of that symphony

 

Read GST Principles for many more principles; the rest of this paper introduces some historically significant contributors to GST.

Abstraction and cybernetics (Ashby)

As Wikpedia said in 2017:

“Despite being widely influential within cybernetics, systems theory and, Ashby is not as well known as many of the notable scientists his work influenced.

W Ross Ashby was one of the original members of the Ratio Club, who met to discuss issues from 1949 to 1958.”

 

And as Ashby wrote in 1956:

"Cybernetics does not ask "what is this thing?" but ''what does it do?" It is thus essentially functional and behavioristic.”

“Cybernetics depends in no essential way on the laws of physics or on the properties of matter.”

“[It] deals with all forms of behavior in so far as they are regular, or determinate, or reproducible.” Introduction to Cybernetics (1956) W. Ross Ashby)

 

Pointing at an entity and calling it a system is not enough.

“At this point we must be clear about how a "system" is to be defined.

Our first impulse is to point at [some repeated behavior] and to say "the system is that thing there".

This method, however, has a fundamental disadvantage: every material object contains no less than an infinity of variables and therefore of possible systems.

Any suggestion that we should study "all" the facts is unrealistic, and actually the attempt is never made.

What is necessary is that we should pick out and study the facts that are relevant to some main interest that is already given.” (Introduction to Cybernetics (1956) W. Ross Ashby)

 

As Ackoff and Ashby said in their different ways.

A group of people doing things is not a system just because people call it a “system” or an “organisation”.

To be called a system, an entity must exhibit (manifest, instantiate, realise) the properties of a system.

Until those properties have been described and observed, the entity is an unbounded, amorphous part of the universe.

In short, an entity is only a system in so far as it realises an abstract system description.

The mark of a good system description is that you can test how well it is realised in real-world phenomena.

 

“Design for a Brain” (1952)

Ashby treated the brain as a regulator that maintains a body’s state variables in the ranges suited to life.

Even a primitive brain must hold or have access to an abstract model of the body’s current state.

Ashby saw the brain-body relationship as an information feedback loop.

The brain receives information from sensors and sends instructions to motors and organs.

The aim is homeostasis – to maintain the state of the body - and to produce other desired effects.

The table below is an expression of these ideas.

Generic structure

Ashby’s Design for a Brain

Active structure

A collection of brain cells interact by

Behavior

playing roles in processes to

State

maintain body state variables by

I/O Boundary

sending/receiving information

Environment

to/from bodily sensors and motors

 

The graphic below separates Ashby’s regulator (brain) from the controlled system (body).

Mind

Body

“Design for a brain”

<wrote>   <abstracts concepts from>

Ashby                 <envisaged>               Brains

<monitor> Body state variables

<control>  Muscles and organs

 

Ashby picked out variables relevant to his interest in the brain as a regulator, putting aside other things you might consider important to being human.

His Design for a Brain book holds an abstract description of a brain, which in turn holds an abstract description of a body’s physical variables.

Just as an engineer’s specification holds an abstract description of a regulator, which in turn holds an abstract description of the physical variables it controls.

 

“Introduction to Cybernetics” (1956)

As Wikipedia said in 2017:

In An Introduction to Cybernetics ‘Ashby popularised the usage of the term 'cybernetics' to refer to self-regulating systems

The book dealt primarily with homeostatic processes within living organisms, rather than in an engineering or electronic context.

Ashby formulated his Law of Requisite Variety stating that "variety absorbs variety, defines the minimum number of states necessary for a controller to control a system of a given number of states."

This law can be applied for example to the number of bits necessary in a digital computer to produce a required description or model.

In response, Conant (1970) produced his so-called "Good Regulator theorem" stating that "every Good Regulator of a System Must be a Model of that System".

 

Every living organism is unique in its infinitely rich and complex detail.

It is hard to overemphasis the importance of what Ashby said about abstraction.

“Any suggestion that we should study "all" the facts is unrealistic, and actually the attempt is never made.

What is necessary is that we should pick out and study the facts that are relevant to some main interest that is already given.” (Introduction to Cybernetics (1956) W. Ross Ashby)

Cybernetics (Weiner)

Norbert Wiener (1894-1964) is the founder of cybernetics - about connecting regulators to machines by a feedback loop.

In 1948, he published Cybernetics: Or Control and Communication in the Animal and the Machine.

The phrase “control and communication” highlights the importance of information flows.

The phrase “the animal and the machine” suggest the principles apply to both animate and inanimate systems.

Cybernetics influenced other systems thinkers.

 

Cybernetics separates a regulator from the “real machine” it monitors and controls.

The real machine is any system that that is to be monitored and controlled.

The controller is another system, here called the regulator to avoid confusion.

Regulator

Real machine

Regulator specification

<forms>          <abstracts concepts from>

Control engineers  <observe and envisage>  Regulator

<monitor and control>  Controlled system

 

A basic principle of cybernetics is that a control system has to hold a description or model of what it controls.

As Conant’s “Good Regulator Theorem” says "every good regulator of a system must be a model of that system".

Brains and businesses can be seen as systems that monitor and strive to direct some things in the real world.

A brain has to form a mental model of what it perceives to be out there through its senses.

A business has to maintain documented models of the entities and events it monitors and directs through information feedback loops.

However, these models contain only a selection of facts or variables abstracted from that what is monitored and directed.

 

Tennis match example

When tennis match officials monitor events in a tennis match, they form mental models of the players’ actions

Match official

Regulator, hold a mental model of

Players’ actions

Machine or controlled system

 

The match officials direct players’ actions according to the laws.

Regulator

Real machine

Laws of tennis

<write>   <abstract rules used by>

LTA  <observe and envisage>  Match officials

<monitor and control>  Tennis match

 

Heating system example

Second example: a thermostat holds a model of a temperature variable

Thermostat

Regulator, holds a physical model of temperature

Heating system activity

Machine or controlled system

 

The thermostat switches the heating system on and off, according to its model of the temperature.

Regulator

Real machine

Thermostat drawings

<draw>   <abstract concepts from>

Engineers  <observe and envisage>  Thermostats

<monitor>  Temperatures

<control>  Heating systems

 

Berrisford’s cybernetic principles

A brain (using animal intelligence) maintains mental models of what it perceives to be out there through its senses.

A business (using information systems) maintains documented models of entities and events it monitors and directs through information feedback loops.

To direct an entity or activity in its environment, a brain or a business must be able to:

1.      Maintain or obtain a model of the state of that entity or activity (the model must be accurate enough).

2.      Gather inputs: detect events that reveal a significant state change (in an acceptably reliable and timely fashion).

3.      Produce outputs: respond to events or state changes by sending directives to the entity or activity (in an acceptably reliable and timely fashion).

4.      Adapt if the external entity or activity does not respond to a directive a reasonably predictable and deterministic way.

Soft systems (Checkland)

The table below maps Checkland’s system to a general structure used in these papers.

Generic structure

Peter Checkland’s Soft System

Active structure

Components interact coherently in

Behavior

activities to meet a purpose by

State

maintaining their integrity and

I/O boundary

sending/receiving inputs and outputs

Environment

to/from each other and external actors

 

The term “soft system” can be read in Checkland’s works as having two meanings.

Sense 1: An empirical system in which human actors play roles; a business usually has many systems of this kind.

Sense 2: A theoretical system, the world-view (Weltenshauung) of an individual or social group.

Ashby taught us every system description is a soft system in the second sense.

We shall argue there is a need to distinguish social systems from social entities.

Discrete v continuous system dynamics (Forrester)

Activity systems are dynamic, meaning that the state of the system changes over time in response to events or forces.

Later papers discuss the modelling of dynamics using two different approaches.

Discrete dynamics – system state advances incrementally in response to discrete events

The logic of system theory can be expressed in a model of discrete entities and events.

E.g. A business information system monitors and directs individual entities and events in its environment.

That system can be described in the form of a logical entity/event model

The model is translated into the software of a transaction processing system.

The coded system is first tested and then implemented as a live/production system.

 

In operation, the system runs in a feedback loop with its environment.

The system:

·         detects events and changes in the environment

·         maintains a model of the entities and events that it monitors

·         sends messages to direct entities and events in the real world.

If the system does not successfully monitor and direct entities and events in its environment, then it is changed or abandoned.

It supports and enables current behaviors, but does not predict their long-term outcomes.

Continuous dynamics - system state advances continually in response to continuous forces

How to model inter-related populations (say wolves and sheep) that are continuously changing?

A popular method, Forrester’s system dynamics, is distilled in the graphic below.

System dynamics

Model of Stocks and Flows

<create and run>                   <idealise>

System modellers     <observe and envisage>     Causal loops

 

The purpose of system dynamics is not to draw diagrams directing designers how to build a system.

It is to mimic or predict the outcomes of the built system - by running the system dynamics model as a simulation.

 

Causal loop diagrams and system dynamics models are high-level abstractions.

They model stocks of entities (wolf pack, sheep flock).

They don’t model individual entities (a wolf, a sheep), unless you count each “1” in a stock total as a model.

They model batches of events (number of sheep killed per time unit).

They don’t model individual events (a single predation), unless you count each “1” in a number of events as a model.

 

You can convert a discrete entity/event model into a system dynamics model by abstraction.

You cannot recover the entity/event model from the system dynamics model.

Because the process of abstraction erases all qualitative attributes (names, addresses, descriptions, dates).

It also erases all instance-level entities, leaving only the quantitative volumes of entity types.

Other ideas and developments

von Bertalanffy discussed other concepts like "emergence", "continual evolution", "goal-directedness" and “complexity”.

Later papers discuss ambiguities in the meanings of these terms.

 

E.g. What is complex, or what implies complexity, is far from agreed.

You might assume that if a system behaves unpredictably, it must complex. Not so.

Complex systems can be predictable; and simple systems can be unpredictable.

People glibly assert that a system is complex, without reference to any description or complexity measure.

The only way to measure a thing’s complexity is by reference to a description of its elements.

Bertalanffy said system elements are discrete, can be classified into kinds, can be counted, and the relationships between them can be described.

“In dealing with complexes of 'elements', three different kinds of distinction may be made: according to their number; their species; the relations of elements.” von Bertalanffy

Which elements do we count? And then, how do we combine those numbers into an overall complexity measure?

There is no widespread agreement; see the “complexity” paper for more.

 

When GST ideas were aired by von Bertalanffy, Boulding and Ashby in the 1940s and 50s, computers were not in the picture.

The subsequent birth of computer science can be seen as a vindication of the notion that there is a cross-science general system theory.

Software systems can be seen as a special application of GST, one that narrows the abstract-concrete (description-reality) gap.

However, they don’t exhibit some features von Bertalanffy’s speculated might be “general” to all systems.

That is why some of von Bertalanffy’s notions don’t appear in this update of GST.

And why homeostasis, a focus of early system theorists, is not presented here as a general system property.

Footnotes

More on GST after Bertalanffy

What more of von Bertalanffy?

He eventually committed to a book (1968) in which he said GST brings us “nearer the goal of the unity of science”.

The book is here (http://bit.ly/174yEk4).

The quotes below are drawn from selected passages you can find at http://www.panarchy.org/vonbertalanffy/systems.1968.html.

“There exist models, principles, and laws that apply to generalized systems or their subclasses, irrespective of their particular kind, the nature of their component elements.”

conceptions appear in contemporary science that are concerned with what is somewhat vaguely termed 'wholeness'.

I.e. problems of organization, phenomena not resolvable into local events, dynamic interactions manifest in difference of behavior of parts when isolated or in a higher configuration, etc.

In short, 'systems' of various order not understandable by investigation of their respective parts in isolation.”

“General System Theory… is a general science of 'wholeness'.”

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

“Information and Feedback: Another development which is closely connected with system theory is that of… communication.

The general notion in communication theory is that of information. A second central concept of the theory of communication and control is that of feedback.”

“Causality and Teleology: You cannot conceive of a living organism, without taking into account what variously and rather loosely is called adaptiveness, purposiveness, goal-seeking and the like.”

“The System Concept: In dealing with complexes of 'elements', three different kinds of distinction may be made: (1) according to their number; (2)  according to their species; (3) according to the relations of elements.”

 

Other sources say:

“Systems theory is the interdisciplinary study of systems in general, with the goal of elucidating principles that can be applied to all types of systems at all nesting levels in all fields of research.

The term does not yet have a well-established, precise meaning.” Wikipedia

“Systems theorists seek to explain the behavior of complex, organized systems from thermostats to missile guidance computers, from amoebas to families.” “Systems Theory” Gail G. Whitchurch, Larry L. Constantine

“Some scholars consider general system theory to be broader than a theory, but rather an alternative Weltanschauung—a unique worldview” (Ruben & Kim, 1975).”

 

Not everybody accepted that GST is valuable.

The schools of systems thinking have different roots and perspectives; different schools hold sway in different regions.

“General system theory, like other innovative frameworks of thought, passed through phases of ridicule and neglect. (Laszlo and Krippner)

 

A respectable summary of GST is quoted below:

"von Bertalanffy.emphasized that real systems are open to, and interact with, their environments, and that they can acquire qualitatively new properties through emergence, resulting in continual evolution.

Rather than reducing an entity (e.g. the human body) to the properties of its parts or elements (e.g. organs or cells),

systems theory focuses on the arrangement of and relations between the parts which connect them into a whole (cf. holism).
This particular organization determines a system, which is independent of the concrete substance of the elements (e.g. particles, cells, transistors, people, etc).
Systems concepts include: system-environment boundary, input, output, process, state, hierarchy, goal-directedness, and information." Principia Cybernetica Web

 

On natural systems and designed systems

A system can be natural: be it physical (a solar system, a hurricane), biological (a tree), or social (a beehive)

Or else designed: be it social (a tennis match) or technological (a bicycle, a computer).

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

 

Natural systems: repeated behaviors

Designed systems: reproducible behavior

Observation of a natural system in operation precedes its description

First, the natural system runs in reality as phenomena instances.

·         The Krebs cycle was a system in operation before it was described.

·         The solar system was in operation before it was described.

.

The solar system can be called a discrete entity – meaning it is separable from the rest of the universe.

Telling you that the orbiting planets form a solar system conveys an additional meaning.

It tells you that the system’s behavior can – conceivably - be tested against a description.

 

Orbiting planets as a system

“The solar system”

<define>       <abstracts features of>

Astronomers  <observe and envisage>  Planets in orbits

 

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.

 

The solar system is composed of a few planets that display regular behaviors.

If/when those regular behaviors cease, that entity will stop being the system we understood it to be.

The description of a designed system precedes its operation in reality.

First, the designed system is described as a set of phenomena types.

·         Microsoft Word had to be described in coded types before it could be used to write a document.

·         A professional tennis match was described in laws before any matches of that type were played.

 

A tennis match can be called a discrete entity – meaning it is separable from the rest of the universe.

Telling you that it is a system conveys an additional meaning.

It tells you that the system’s behavior can – conceivably - be tested against a description.

 

Tennis match as a system

Laws of tennis

<write>   <abstract features of>

LTA  <observe and envisage>  Tennis matches

 

The correspondence of 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.

 

A tennis match is composed of players and officials that display regular behaviors.

Without those regular behaviors, there is nothing describable as tennis match.

 

 

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