Emergence and self-organisation: Informal definitions

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Emergence and self-organisationInformal
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 dont 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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Whats 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 Aristotles ideas and legacy
• Non-human animals could be reductively explained
  as automata (Descartes De homine, 1662)
• Matter from fundamental particles (Dalton, c1803)

http//www.anyalarkin.com/alblog/wp-content/upload
s/2012/04/Anya-automaton1.jpg

• 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.edc.ncl.ac.uk/assets/graphics/montecarl
o.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
e.g., A vortex does not exist without flow
http//earthobservatory.nasa.gov/Newsroom/NewImage
s/Images/Australia_AMO_2006156.jpg
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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/0609/0609
011.pdf
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An observation on time-bands
Burns et al, 2005 http//www.cs.york.ac.uk/
ftpdir /reports/YCS-2005-390.pdf

• 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

curriculum
Lecture
New slide
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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 system
• Different properties apparent at different scales
• and Scope
• How / 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.pd
f
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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
• Well 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 dont 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 cant cope with the ideas of emergence
  and complexity
• full stop!

Stepney et al, ICECCS 2006
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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/note
books/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
• Winfrees study of rhythms and oscillation in
  biological systems
• Computer science use in unsupervised learning

Shalizi, 2001, http//cse.ucdavis.edu/cmg/compmec
h/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,,538123
5,00.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