One of a hundred papers on the System Theory page at http://avancier.website.

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Contents

Preface. 1

Weiner 1

Ashby. 3

Turing. 5

Preface

Cybernetics is the science of systems in which biological or mechanical actors process information.

It was established after the second world war - then soon embraced within a broader system theory movement.

The general idea is of an information feedback loop.

· a control system receives messages that describe the state of a target system.

· the control system responds by sending messages to direct activities in the target system.

The information, encoded in messages and memories, describes and/or directs something in the world.

The general idea is found in both organic and mechanical systems

· A missile guidance system senses spatial information and sends messages to direct the missile.

· A brain holds a model of things in its environment, which an organism uses to manipulate those things.

· A business database holds a model of business entities and events, which people use to monitor and direct those entities and events.

· A software system holds a model of entities and events that it monitors and directs in its environment.

The Ratio Club, which met from 1949 to 1958, was founded by neurologist John Bates to discuss cybernetics.

Many of its 21 members went on to become prominent scientists - neurobiologists, engineers, mathematicians and physicists

It members included Alan Turing and Ross Ashby.

(In the 1950s, Turing envisaged that computers would give us insights into how the brain works.

Here, the brain’s ability to typify and predict things is more interesting than its workings.)

Abstraction of description from reality

For some, understanding cybernetics requires making a paradigm shift as radical as is needed to understand Darwin’s evolution theory.

People point at a machine or a business in the real world (like IBM) and say "the system is that thing there".

To Ashby, the question is not so much "what is this thing?" as ''what does it do?"

Classical cybernetics is about systems that exhibit regular or repeatable behaviors.

The concrete thing that is IBM can be (can manifest, instantiate, realise) countless different systems.

“A system is any set of variables which he [the observer] selects”. Ashby

A concrete system contains actors and their actions on selected objects/variables.

An abstract system contains roles and rules that actors and their activities adhere to in acting on those objects/variables.

E.g. The abstract roles and rules of the stickleback mating ritual are realised by countless pairs of sticklebacks.

An abstract system hides or ignores the infinite complexity of any real world actors and activities that realise the system.

E.g. In describing and testing the mating ritual, no attention is paid to the complexity of a stickleback’s internal biochemistry.

These system theory concepts are ubiquitous in modern systems analysis and design methods.

This table presents them in a way that can be used in discussion of social entities.

Abstract social system	A set of roles and rules (the logic or laws actors follow)
Concrete social system	Actors playing the roles and acting according to the rules

There is a many-to-many relationship between abstract systems and concrete entities.

One abstract system may be realised many times. E.g. the roles and rules of tennis may be realised in many concrete tennis matches.

Conversely, a concrete entity may realise any number of abstract systems. E.g. a pair of people may realise many tennis matches and many games of chess.

A social group in the real world is distinct from any abstract social system it realises.

A social system description hides the infinite complexity of the actors and activities in a social group.

And to be scientific, we must describe a system in a way that enables us to test whether a social group instantiates it or not.

In short, classical cybernetics describes a system by

· typifying actors in terms of roles they play

· typifying activities in terms rules that actors follow.

· typifying the values of acted-on things in terms of variable qualities or values.

Cybernetics

Roles, Rules & Variables

Systems thinkers <observe & envisage> Actors, Activities & Values

Differentiation of system state change from system mutation

Ashby insisted we should on no account confuse two kinds of change.

	Changes	For example
System state change	the value of at least one state variable	homeostatic regulation of values to stay within a desired range
System mutation	the type of at least one variable or behavior.	re-organization: changing the variables or the rules that update their values.

Weiner

Norbert Wiener (1894-1964) founded cybernetics.

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

He coined the term Cybernetics for the concept of natural and artificial organisms steering themselves using feedback.

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

He designed self-steering anti-aircraft firing system using radar feedback.

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

A simple homeostatic system is composed of two components:

· a control (or regulatory) system

· a target system (or “real machine”).

Much as humans abstract descriptions from realities, so do control systems.

The control system monitors a selection of variable facts observable in a target system.

Heating system example

A bimetal strip thermostat models the temperature of its environment.

It switches a heating system on and off, according to the state of its model.

Abstract system

Concrete system

Control system

Model of target system variables

A thermostat’s measure of temperature

Target system

Variables monitored

Variables controlled

An air temperature value

A heating system is on or off

Observations:

Early system theorists were especially interested in homeostatic systems, which maintain their state via feedback loops.

Since then, cybernetic ideas have succeeded brilliantly in other spheres and applications.

Tennis match example

Tennis match umpires monitor events in tennis matches and direct players’ actions according to the laws.

The laws are defined by the Lawn Tennis Association.

Abstract system

Concrete system

Control system

Laws of Tennis

An umpire

Target system

Variables monitored

Variables controlled

Particular players and ball behavior

Particular players’ behavior and match score

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.

Ashby

W. Ross Ashby (1903-1972) was a psychologist and systems theorist.

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

“Ashby popularised the usage of the term 'cybernetics' to refer to self-regulating systems” Wikipedia 2017

Understanding Ashby’s ideas helps you to understand much else in the field of systems thinking.

The eight ideas below are applied today in methods and modelling languages for enterprise, business and software architecture.

1. Systems are abstractions

2. Systems are deterministic

3. Cybernetics is behavioristic

4. System mutation change differs from system state change

5. Cybernetics is about information rather than energy flow

6. The brain can be modelled as a control system

7. Variety is a measure of complexity

8. Variety absorbs variety - the law of requisite variety

Read Ashby’s ideas for more explanation of the eight ideas above.

Turing

Alan Turing (1912 –1954) was computer scientist, mathematician, logician, cryptanalyst, philosopher, and theoretical biologist.

The members of The Ratio Club were interested in understanding biological brains and developing artificial intelligence.

“Turing led three different talks.

In 1950, Turing introduced the Turing Test and focused on how intelligent machines might be developed.

Turing suggested using adaptive machines that could learn over their lifetime.

In 1952, Turing described his then unpublished work on reaction-diffusion models of morphogenesis.

This launched him into new directions of theoretical biology and was incredibly influential in the field of computer modelling.

In a letter to William Ross Ashby, he said: "In working on the ACE [Automated Computing Engine] I am more interested in the possibility of producing models of the action of the brain than in the practical applications of computing."

Observations:

In the 1950s, Turing envisaged that computers would give us insights into how the brain works.

Here, the brain’s abilities are more interesting than its workings.

Systems thinking involves typifying actors using roles, activities using rules, and qualities/values using variables.

The types in systems descriptions range all the way from loosely-defined human roles to rigid software classes and data types.