Emergence and self-organisation:

Informal definitions

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Emergence …

Although each effect is the resultant of its components, we cannot always trace the steps of the process, … , we propose to call the effect an emergent ... instead of adding measurable motion to measurable motion, or things of one kind to other … of their kind, there is a cooperation of things of unlike kinds ... The emergent is unlike its components … these are incommensurable, and it cannot be reduced to their sum ...

Lewis 1875, first use of the term “emergence”

Fire, life, magnetism, heat … were all once thought … to be due to their own dedicated substances — phlogiston, vital fluid, magnetic fluid, caloric, and so on — but are now understood as emergent phenomena of … natural processes.

Bickhard 2002

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Recap: some introductory ideas

• Emergence Behaviour observed at one scale is not apparent at other

scales

• Self-organisation Structures that emerge without systematic external stimuli

• Explore these informally …

• Key issue: is emergence a natural phenomenon or an artefact of observation? Can we answer this?

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Emergence is not surprise

• Some early work defined emergence as surprise The surprising effects that emerge when a lot of agents

come together when the football crowd does a Mexican wave that single-cell amoebae can operate as a multi-cell organism that quantum physics gives rise to Newtonian laws

• OK – I was surprised the first time

• Surprise is too rooted in personal experience If my only experience of a crowd produced a Mexican wave,

my crowd definition includes pulsating surface behaviours

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Who studies emergence?

• Philosophers of mind how the mind emerges in the physical brain how intelligence emerges from unintelligent matter

• Biologists (philosophers of biology) how life emerges from inanimate matter

• Computer scientists (ALife community) how properties analogous to mind or life might emerge on

non-biological substrates (computers)

• Amongst others …

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Defining Emergence

• They agree on just two things We need a consistent definition of emergence We don’t have one

• “The whole is other than the sum of its parts” Metaphysics (Aristotle, Ancient Greece) Phenomenology (Jung, Hegel, late 19th century)

Applied in solid state physics (Anderson, 1970)

• Recognition that parts of science are resistant to understanding through reductionism

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What’s wrong with reductionism?

• The basics are there: Quantum phenomena give rise to physics Physical phenomena give rise to chemistry Chemical phenomena give rise to biology, geology, etc. Biological phenomena give rise to society

At which point, humans observe, and see patterns

• Abstraction allows some prediction and replication• But only up to a point

Cannot model with sufficient precision Heisenberg uncertainty, the mathematical limit on what can be

known about a physical system Non-determinism (e.g. in quantum physics) Impossibility of capturing the precise start state

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Reductionism ignores dynamics

• Consider some examples: Growth

phenotype emerges from structure and dynamics of growth rules

Intelligence emerges from structure and dynamics in the nervous system

Sociology emerges from structure and dynamics of social organisms

• Keep checking as we look at new examples Can you explain the emergent behaviour by reduction?

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Reductionism versus phenomenology

• Reductionism dominated science to 19th century Despite Aristotle’s ideas and legacy

Non-human animals could be reductively explained as automata — (Descartes: De homine, 1662)

Matter from fundamental particles (Dalton, c1803)

• Observation and theory challenged reductionism e.g., many new fundamental particles

• Phenomenology in science Empirical observations are related in ways consistent with

fundamental theory but not directly derived from it Monte Carlo modelling, PDEs, etc. Used in biology, particle physics, etc.

http://www.anyalarkin.com/alblog/wp-content/uploads/2012/04/Anya-automaton1.jpg

http://www.edc.ncl.ac.uk/assets/graphics/montecarlo.jpg

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Phenomenology and emergence

• Phenomenology in science focuses on modelling to mirror observed behaviour Guess key components

A surrogate for full understanding of observed behaviour Cannot say what a model means in terms of natural phenomena

Estimate some rates, feed into equations, guess what it means

Some support for prediction Often later verified by observation

• Like Aristotle, our sense of emergence is more fundamental System properties and behaviours are an inherent property

of collections of components over time and space

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How can anything new emerge? Importance of process

• Reductionism is founded on a “metaphysics of substance” Static particles that just divide or combine

• Process is vital to emergence (and scientific understanding) Temporal and physical context and scale are vital It is point-particles or entities that are artificial

persistent instances of organisations

Bickhard, in Downward Causation, 2000

http://earthobservatory.nasa.gov/Newsroom/NewImages/Images/Australia_AMO_2006156.jpg

e.g., A vortex does not exist without flow

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Levels in emergence

• Emergent properties are irreducible No reductionist explanation

• Systems theory e.g., Checkland, 1981

System level language is meaningless at component level Cannot derive system description from component

description

• Each level has its own structure and dynamics Longer time scales reveal relatively stable high-level

patterns Larger scale reveals patterns with extent and movement

Such as vortices

Ryan: http://arxiv.org/PS_cache/nlin/pdf/0609/0609011.pdf

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An observation on time-bands

• Time scale of emergence

Within the context of any particular band: Activities within lower (faster) bands are instantaneous Activities within higher (slower) bands are static

Burns et al, 2005: http://www.cs.york.ac.uk/ ftpdir /reports/YCS-2005-390.pdf

Lecture

New slide

curriculum

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Example: biological levels of emergence

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Resolution and scope

Emergent properties are simply a difference between global and local structure.

• Instead of layers / levels, consider Resolution … Characteristic of representation of systemDifferent properties apparent at different scales

• … and ScopeHow / where the system boundary is drawn

New properties arise if system encompasses many components

• Time defines dynamics

Ryan, 2006

http://arxiv.org/PS_cache/nlin/pdf/0609/0609011.pdf

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Levels, Resolution and Scope

• Resolution and scope are useful concepts Macro-state is either wider (scope) or coarser (resolution)

than the component state

• Levels are also useful Clear discontinuity in descriptions of system and

components “Macro-state” implies scale difference

• Level, scope and resolution are just views Observing properties or behaviours at a coarse resolution Observing more of the system (wider scope)

• This is an open academic discussion We’ll return to it after entropy!

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Types of emergence

• Much discussion of types of emergence Weak, strong, intrinsic, extrinsic

Often not very useful

• e.g., intrinsic emergence (Crutchfield): No external observation needed

“the system itself capitalises on patterns that appear”

• e.g., strong emergence (Bedau) Allied with downward causation

Weaker forms admit those who don’t like downward causation

see, e.g., Stepney et al, ICECCS 2006

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Causality among levels, scopes, resolutions

• It is ‘obvious’ that coarser, higher level (… ) patterns are caused by finer, lower level (… ) dynamics Upward causation

• Downward causality is more controversial At some temporal or spatial scale, global patterns affect

local behaviours Context is vital for emergence

To some researchers, downward causation is intrinsic To other researchers it is too inexplicable for credibility

But some can’t cope with the ideas of emergence and complexity …

… full stop!

Stepney et al, ICECCS 2006

Self-organisation

“Is the Mexican wave really a ripple of excitation?”

Cartwright, http://www.europhysicsnews.com/full/41/article3.pdf

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Examples of self-organisation

• Social activities Construction by social insects, flocking, crowd dynamics

• Dissipative structure e.g., a thermodynamically-open system operating far from

equilibrium in an environment with which it exchanges energy

e.g., BZ reaction, hurricanes, turbulence, convection

• Some CAs and evolutionary computations eg cyclic CAs, swarms

• Some authors include phase transitions, turbulence, ecosystems, adaptation, natural design principles …

Shalizi: http://www.cscs.umich.edu/~crshalizi/notebooks/self-organization

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Self-Organisation

• Idea probably from Descartes (1637) Before that, order arises by chance, given time and space,

• “Self-organisation” coined by Ashby (1947)

• Ashby considers organisation to be invariant Organisation f derives from the functional dependence of a

current state Sc on a past state Sp and some inputs I

f : Sp × I Sc

W. Ross Ashby, 1949, 1962: reproduced at csis.pace.edu/~marchese/CS396x/Computing/Ashby.pdf

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Self-Organisation

• Ashby states that self-organisation is apparent if: in two regions of state space, f is approximated by

organisations g and h

g : Sg × Ig Sg

h : Sh × Ih Sh

system dynamics drive the system from g to h

• Self-organisation is observed locally in a system with globally-invariant organisation Self-organisation is thus an emergent property due to the

scope of consideration of the larger system

• Much subsequent work ignores Ashby Preference for vague, informal definitions

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Variants on self-organisation

• Claims and counterclaims on whether systems self-organise

• A few contribute to understanding: Hypercycles to explain co-operation among competing

individuals

Winfree’s study of rhythms and oscillation in biological systems

Computer science use in unsupervised learning

Shalizi, 2001, http://cse.ucdavis.edu/~cmg/compmech/pubs/CRS-thesis.pdf

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Self-organisation and emergence

• Self-organising systems display emergent properties Patterns at a higher level, coarser resolution or wider scope

• Dicty amoebae self-organise [later]

an emergent slug and emergent fruiting behaviour

• Social insects self-organise to achieve construction, effective navigation, foraging

• Crowd behaviours in higher species

If this does not convince you that

dynamics are essential…

http://www.news.com.au/common/ imagedata/0,,5381235,00.jpg

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A working definition of emergence

• A system with levels Scales, resolutions …

At each level, granularity of space and time are different

• Levels have different languages The concepts needed to describe each level are distinct

• System is neither random, nor in a steady state Constant flows of energy, matter… Dynamics essential to emergence

• At lower level, components may tend to self-organise

• Try looking at the later examples in these terms…

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Putting it all together

Prokopenko et al, An information theoretic primer, 2007