Introducing cybernetics

Copyright 2016 Graham Berrisford. One of several hundred papers at http://avancier.website. Last updated 15/09/2018 13:45

 

This paper introduces some of the terms and concepts of cybernetics.

Contents

Preface. 1

Weiner 1

Ashby. 3

Alan Turing. 4

Further reading. 5

 

Preface

After the second world war, the general system concept became a focus of attention.

The science of cybernetics was established, and then embraced within a broader system theory movement.

Cybernetics is the study of systems - natural and designed – and how they interact with each other .

 

Cybernetics is about systems in which biological and/or mechanical actors perform regular activities.

Those activities include consuming, remembering and producing information.

The information is contained in signals/messages and memories that describe or direct some part of reality.

E.g. A control system consumes signals/messages that describe the state of actors in a target system.

The control system produces signals/messages that direct the activities of actors in a target system.

Thus, the control and target systems are connected by an information feedback loop.

These cybernetic ideas appear in systems of many kinds - biological, business, social and software.

 

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 Ross Ashby and Alan Turing – two of the three thinkers discussed below.

Weiner

Norbert Wiener (1894-1964) founded cybernetics – about how regulators monitor and control behaviors using feedback loops.

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 or machines.

 

A simple homeostatic system is composed of two components - a control (or regulatory) system and a target system (or real machine).

A control system models a selection of variable facts (such as temperature) observable in a target system.

E.g. 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.

 

Control system

Model of target system variables

Thermostat

Target system

Target system behavior

Heating system on/off

 

The target system is any entity whose behavior is to be monitored and directed.

 

Control system

Target system

Regulator specification

<forms>                         <realised by>

Control engineers  <observe and envisage>  Regulator

<monitor and control>  Regulated system

 

A basic principle of cybernetics is that a control system has to hold a description or model of the target system.

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 entities and events it monitors and directs through information feedback loops.

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

 

Heating system example

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

A control system models a selection of variable facts (such as temperature) observable in a target system.

E.g. 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.

 

Control system

Model of target system variables

Thermostat

Target system

Target system behavior

Heating system on/off

 

The same can be represented in a different graphic thus:

 

Control system

Target system

Thermostat drawings

<draw>                      <realised in>

Engineers  <observe and envisage> Thermostats

<monitor>  Temperatures

<control>  Heating systems

 

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.

 

Control system

Target system

Laws of tennis

<write>                   <realised by>

LTA  <observe and envisage> Match officials

<monitor and control>  Tennis match

 

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

 

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

In short, cybernetics is about deterministic systems.

 

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

Ashby recognized the importance of distinguishing a system from a machine (natural or designed) that realizes it.

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

Our first impulse is to point at [a machine] and to say "the system is that thing there".

This method, however, has a fundamental disadvantage: every [machine] has 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.” Ashby 1956

 

Ashby’s v iew

Abstract system descriptions

<create and use>                   <idealise>

Systems thinkers <observe & envisage> Concrete entities

 

To apply Ashby’s system theory is to apply the scientific method

You observe or envisage a system in the real world – an empirical system – an instance.

You model it in an abstract system description - a theoretical system – a type.

 

To model a real world system is to model its state and its behavior.

You model the state as variables whose values can be measured (e.g. the positions of the planets).

You model the behavior as processes (e.g. the orbits of the planets) that maintain or advance variable values

The model is a type; it hides the infinite complexity of real-world actors and activities that instantiate (or realise) the model

If and when the concrete system runs in reality, you can test that real-world entity against what the abstract system predicts.

 

Ashby insisted we distinguish two kinds of system change, which need different names here.

·         Regulation: regulating the values of defined state variables, usually to stay within a desired range.

·         Re-organization: changing the state variables themselves, or the rules that update variable values.

 

Ashby’s Law of Requisite Variety defines the minimum number of states necessary for a control system to control a target system with a given number of states.

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".

 

Observations:

The Good Regulator theorem was proved by biological evolution long before Conant articulated it.

Animal brains maintain mental models of things (food, friends, enemies etc.) they care about in their environment.

These mental models must be accurate enough to enable the animals to monitor and manipulate those things.

Read Ashby’s ideas for more.

 

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.

 

Cybernetics

Roles, Rules & Variables

<create and use>                   <idealise>

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

Further reading

This paper has introduced some of the terms and concepts of cybernetics.

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

If you want to read this work in sequence, move on to System Dynamics.

You can find a list of cyberneticians at http://www.asc-cybernetics.org/foundations/cyberneticians.htm.

 

 

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