Spring School Complexity Science

Introduction toComplexity Science

Working with Systems

Seth Bullock, 2006

Systems

Systems science is clearly concerned with systems. Two kinds are relevant here…

We can think of the things in the world that provide the demand for systems science: problem systems… genomes, cities, corporations, the health service

Sometimes the things that we build to solve these problems are also thought of as systems… databases, simulation models, virtual

environments, etc.The word system is clearly a very general term that can be applied to many, many things. What do we mean by it?

Seth Bullock, 2006

A graph representation can capture the structure of a simple system.

What is a System?

At root a system is a set of individual components that are linked by relationships of some kind to form a whole.

City Centre One-Way System

Nodes might represent road junctions, arcs the roads connecting them…

Web of Component Supply

…or firms connected by supply and demand relationships…

Genetic Regulatory Network …or genes involved in a network

of +ive and –ive genetic regulation.

+ive

-ive

Other definitions exist, but this captures the various levels of description involved studying any system: part and whole, system and its surroundings, etc.

Seth Bullock, 2006

sam

ple

1

sam

ple

2

sam

ple

3

sam

ple

4

A Biological Example

Many genes code for proteins that either promote or inhibit the transcription of other genes. Together, such genes form genetic regulatory networks.can we infer the structure of these networks from

micro-array data, samples of transcription factor levels?

time

level is the data too noisy

or irregular for this to work?could we simulate a particular real network?could we use simulations to discover how these

types of genetic regulatory network behave in general ?

Seth Bullock, 2006

A Geographical Example

One of the main factors influencing the design of built environments such as airports, museums, libraries, etc., is the way in which pedestrians move through these spaces.How can designers structure environments such that the behaviour of pedestrians is appropriate or desirable? ensuring safe & timely exit and escape behaviour avoiding bottlenecks, congestion, crowding, etc. maximising impact of advertising space, facilities,

etc. Virtual environments and models of pedestrian movement can provide designers with feedback before bricks are laid.How can we ensure that these computational solutions are fit for purpose – usable, accurate, flexible?

Seth Bullock, 2006

An Engineering Example

Many engineered products are complex assemblies of sub-components manufactured by many different companies.For example, JPL, Lockheed, and Boeing, among others, collaborated on the design of the Genesis 11 spacecraft. Effectively tracking design

changes and their ramifications requires understanding how the relations between components of the system reflect the relations between the firms collaborating to build it.How might complexity science improve the

management of this information?

Seth Bullock, 2006

A Medical Example

In 2001, an outbreak of foot & mouth (a disease that affects several species of livestock) cost the UK ~£5bn:within 14 days it had covered the entire country

at its height nearly 50 cases a day were being detectedmillions of animals were slaughteredhundreds of farmers lost their livelihoodsthe rural & tourism industries lost billions of pounds

A poor understanding of livestock transportation, disease behaviour, and vaccination, coupled with bureaucratic delays & poor co-ordination created a rapacious epidemic.Could we have reduced the impact of foot & mouth?

Seth Bullock, 2006

A Science of Systems

There have been several attempts to develop tools to help solve problems like the ones listed on the previous slides.Such efforts are kinds of systems science:

cybernetics, systems theory, dynamical systems theory, complexity, control theory, information theory, etc.Each of these approaches attempts to provide

frameworks for thinking about and analysing systems in general.Motivating these endeavours is an assumption that the systems mentioned in earlier slides are fundamentally similar – their differences are merely superficial. If this is true, is there something to be gained from studying such systems in general, rather than individually?

Seth Bullock, 2006

Levels of Description

It is important to appreciate the subjectivity of a systems perspective – there is no single “correct” level of analysis. For instance, human DNA can be understood as… a set of genes, a string of bases, a large

molecule, etc.Each perspective is valid, but each differs from the others in important respects, and is relevant at different times.Often the success of a particular approach is crucially dependent on choosing an appropriate level of description: detailed enough to capture critical system

behaviour yet abstract enough to avoid unnecessary

complexityWhich aspects to visualize, model, etc., depends on the nature of the problem that is being solved.

Seth Bullock, 2006

Describing System Structure

The implications of a system’s structure will tend to be domain-specific, but there are also general considerations: types of atomic entity: how many? what kind?

e.g., herds of cattle & sheep, diseases, vaccines types of interaction: how many? what kinds?

e.g., transportation, infection, vaccination, etc. type of connectivity: sparse (rural) vs. dense

(city) e.g., road & rail networks, infection vectors, etc.

degree of uniformity: homogeneous vs. heterogeneous

e.g., random or grid-like vs. structured in some way

inputs & outputs: how many? what kind?e.g., open system vs. closed system?

Seth Bullock, 2006

Entire Cognitive &

Visual System

Sub-systems & Coupling

It is often useful to consider an entire system as divided into parts, e.g., because they seem relatively independent.E.g., the eye & brain can be considered to be a single cognitive system, or to be distinct sub-parts of the system.

E

S

MB

They exchange signals via nervous tissue, the eye supplying sensation while the brain controls the ocular muscles.Likewise, robot and environment interact in many ways, e.g., via sensors and motors.

Sub-systems that influence one another in this way are said to be coupled.

E

S

MR

Seth Bullock, 2006

The Eye of the Beholder

Like choosing a level of description, deciding what counts as inside or outside a system, or how to divide one into sub-systems is a subjective issue. For example……it may be useful to consider a tool to be part of the agent, or a robot’s wheels part of the environment, etc.We often treat an external system as a part of our body… prosthetic devices such as eye-glasses,

pacemakers tools (e.g., a hammer), vehicles (e.g., a bicycle, a

car)…or sometimes consider a body part to be external to us… e.g., when a body part is anaesthetised or fails

somehowIndeed, sub-systems tend to be noticed as separate only when they fail in some manner…

Seth Bullock, 2006

Hierarchy vs. Anarchy

An important distinction separates systems that exhibit a hierarchical structure from those that are disordered.Many man-made systems feature central controllers, or higher authorities that organise lower-level entities. Boss

Team Leader

Team Members

Team Leader

Team Members

Structures like these are intended to generate well-ordered behaviour.In contrast, many natural systems are not structured in this way, yet are still capable of generating well-organised, coordinated behaviours.Many Identical Team MembersFor example, the self-organisation of ant colonies, or traders at the New York stock exchange.

Seth Bullock, 2006

Describing System Behaviour

It is typically more important to characterise a system’s actual behaviour, rather than it’s structure.Some systems have no behaviour (e.g., a fixed classification system), but most do. some systems are static until acted upon in some

waymany man-made computational systems, for instance

in contrast, some systems have an intrinsic dynamic

a brain? an ant-colony? economy? online community?

Like structure, what behaviour is attended to is subjective. long-term, short-term, low-level, high-level, etc.,

etc.In what ways can we classify system behaviour?

Seth Bullock, 2006

Stability

In many cases, we wish to understand under what conditions a system will remain stable.

will a newsgroup remain robust as new users are added? will an ecology remain stable as new species are

added? is the economy crashing? will a stock retain its

value? is the market for our product changing? how?

In fact, it is often not stability per se that is of interest, but the extent to which a system has departed from stability.How is the system being perturbed? How is this perturbation being coped with? What results from it?Are we able to alter the system? Can we effectively change it in desired ways?

Seth Bullock, 2006

Emergence

The behaviour that a system exhibits at one level of description may be very different from that at other levels.Systems that appear disordered at a low level (such as ant colonies, crowds, economies, etc.) may never-the-less exhibit ordered behaviour at a higher level. For example: Jupiter’s Great Red Spot: a huge gas cloud termite mounds, bee hives, wasp nests efficient market prices: the “invisible

hand” traffic jams, crowd behaviour, fashion

cycles

When high-level ordered behaviour arises from the un-coordinated actions of lower-level entities, it is termed self-organization or emergent behaviour.

Seth Bullock, 2006

Adaptation

Adaptive systems change over time such that they come to suit their environment – they adapt to their surroundings.Evolution by natural selection is the primary example of an adaptive process, but many other types exist:Learning: e.g., shaping an organism’s tastes,

fears, etc. Imitation: e.g., trading behaviour on a stock exchangeCompetition: e.g., pop bands compete for an audience

Even a system as simple as a lawn can exhibit adaptive behaviour, “coevolving” with pedestrians until stable paths are achieved.

Seth Bullock, 2006

Behaviour from Structure?

So far we have talked about structure and behaviour separately, but it is clear that they are intimately linked. How does a company’s management structure

influence its behaviour? It’s flexibility, quality control, creativity?How does Soton’s traffic network influence rush hour?How does the human genome influence morphogenesis?Will a particular virtual reality encourage collaboration?Can we confidently make changes to a system’s structure in order to bring about desirable changes in behaviour?

In order to answer this type of question, we need to do more than just describe a system’s structure & behaviour.