Transcript Self-Organization, Weak and Strong Emergence, and the

Self-Organization,
Strong and Weak Emergence, &
Spatial Planning Patterns at the
Metropolitan Scale
David C. Prosperi
Henry D. Epstein Professor
Florida Atlantic University
Fort Lauderdale, FL 33301
[email protected]
“the majority … were attracted less by the
theoretical and philosophical ideas enfolded in
the TCS … but more by some of the
methodologies associated with the study of
complex systems”
Portugali, 2006, p. 651
‽ the need for a theoretical perspective
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Introduction
My 15 (Pondering) Minutes
The Emergent
Pattern I Focus
On
Separation
Self-Organization
& Emergence
Employment
Patterns in South
Florida
Conclusion &
Discussion
Weak Emergence
Finding the
Nexus
References
Strong
Emergence
dcp’s Left-Sided Brain
• The Object of Planning: To arrange, re-arrange or
shape/advocate/modify elements of a system in
such a way to enable macro-properties of urban
regions to be at adequate levels
• From URP 6840: Learning Agents SelfOrganizing, through a Complex Adaptive System,
realizing Emerging Patterns to reach the Edge of
Chaos in an open, non-linear, disequilibrium
environment, amplifying or dampening effects by
examining feedback of biogeographic barriers
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Some Typologies About Planning
(from Reading, Portugali, Batty, de Roo & Silva)
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It is the Frame That Matters
(to me)
• New Tropes (interaction & networks, emergence, adaptive
innovation and criticalization)
– Goldstein, Richardson, Allen & Snowden, E-CO Annual 2006
• Equilibrium is over rated as a complaint about previous
frameworks
• Emergence is About Scope, Not Scale (Ryan, 2006)
• See Emergence as a Metaknowledge (David, Courdier
>2007)
• Self-Organized Similarity, the Evolution of Groups of Similar
Species (Scheffer & van Nes, 2006)
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Next
What are Macro-properties
Bogart
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Bourne
Others
(Krugman,
Allen,
Portugali,
Batty,
Prosperi,
Marshall)
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My Focus
• Employment
Patterns
Of Metropolitan Regions
• Something that is observable at the scale of the urban
region
– Hierarchy of Shopping Centers
– Hierarchy of Employment Centers
• 30-40% of overall employment is in these centers
– Hierarchy of Roads
– Social Spatial Patterns
– Transport Systems, including Airports
• Some, but not all, follow Zipf’s Law
• Clearly, a “resultant”, probably an “emergent pattern”
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Bogart’s Table
Criterion
Benchmark
Employment in Centers
Employment is distributed over the metropolitan area;
30 to 40% of it is located in identifiable employment centers.
Downtown remains the largest center, but its dominance is attenuating downwards
Employment centers are relatively specialized and unique
Commuting
25 minutes on average, 85% less than 45 minutes
Distances have increased, but time has not (decentralized jobs)
Density
Average person lives in areas of 3,000/sq mi / 4.6 persons per acre
Average person works in areas of 4,000/sq mi / 6.2 persons per acre
1/3 live with 5 miles of CBD, 40% of employment is within five miles of CBD
Congestion
Has increased;
Typical commuter spends 47 hours/year “stuck” in traffic
Plans for Buildings
Sports, convention centers, designed to attract business travellers and tourists both from “within” and
“outside” the metro area
Universities
At least one high quality university
Segregation
Quite segregated by race, but falling
Quite segregated by income, and it persists
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Almost There …
• Krugman
• Allen (part on intra-urban variation)
• Bourne
• Portugali
• Batty (metaphors – schelling, networks, systems over time)
• Marshall (evolutionary development)
• But, the EMERGING winner (so far, according to me) is: -
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Santa Fe Institute (Geoffrey West)
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Urban Science v. Urban Theory – only way to understand is to know deep structure, there is a set of a
few very simple equations. These are the laws that automatically emerge whenever people
“agglomerate”. So, by these rules, he can make precise predictions about the number of violent crimes
and the surface area of roads in a city in Japan with 200,000 people.
Real purpose of cities, and the reason cities keep on growing, is their ability to creative massive
economies of scale, just a big animals do (cities are like elephants)
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So, as the city doubles, it requires an increase in resources of only 85%
Densely populated places require less energy; small green places require more
When a city doubles in size, every measure of economic activity increases by approximately 15% per capita (i.e., folks in bigger cities
will do 15% more of everything) – this is the value of economic interactions
Also true for social problems – 15% increase in violent crimes, traffic and AIDS. What this tells you is that you can’t get economic
growth without a parallel growh in the spread of things you don’t want).
Large not necessarily good, however. Many fast growing cities – done away with public places in favor of suburban areas – are
characterized by below-average levels of income and innovation (as measured by the production of patents); The same sidewalks
that lead to knowledge trading also lead to cockroaches
SUPERLINEAR SCALING: increased output of people living in larger cities. Wobbles at lower levels, then
becomes a steep slope emerges from positive feedback loop of urban life – a growing city makes every
one is that city more productive, which encourages more to people to move to the city, and so on.
Good reason why animals slow down with size. Requires energy.
Current humans requires about 11000 watts. Not sustainable.
Mumford: megalopolis is the last stage in the classic style of civilization. But, technology changes rules.
Cliffhangers and creativity. Cycles are getting faster --about 15 years between big innovations.
Not all agree: Suburban job growth folk: SUSPECT THAT THIS IS A DEFINITIONAL PROBLEM.
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My Take …
Things I Could Do
• Write a Complexity
History
Emerged Properties
More Than One
Center
• Focus on Particular
Set of Multiscalar
Interactions
Rank Order of
Centers
• Explore in More Detail
Complexity Theory
Concepts
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Functional
Specialization
40% of
Employment in
Centers
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Next
Complexity Concepts
Emergence
SelfOrganization
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• Weak
• Strong
Complexity
Economics
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Complexity Theory Attributes
• It is a system. There is a WHOLE
• Open – urban regions subject to many forces, some
internal (local), some external,
• Non-Equilibrium – we accept that a perfect, efficient,
anything cannot be achieved (due to both natural
features (rivers) but also due to path dependency and
other accidents of history (see Batty)
• “Ruled” by self-organization, which MAY include
features of emergence
• Multiscalar dynamics in ecology, economics, and
governmental systems
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The Research Problem
From Wikipedia
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What?
Definition (Wikipedia): is a process of
attraction and repulsion in which the
internal organization of a system,
normally an open system, increases in
complexity without being guided by
an outside source.
Sometimes self-organization is
conflated with that of the related
concept of emergence.
Properly defined, however, there may
instances of self-organization without
emergence and emergence without
self-organization, and it is clear from
the literature that the phenomena
are not the same.
The link between emergence remains
an active research question.
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• Clear from the Literature??
• Remains an Active Research
Question
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Approach
Separate
Find Nexus
• Strong Emergence in Self-Organizing
Systems
• Not Very Well Treated in the Literature
• Weak Emergence in Self-Organizing Systems
• This is the “Normal” Way
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• ???
Looking for
Examples
• ???
Looking for
Examples
SelfOrganization
with
Emergence
SelfOrganization
without
Emergence
Controlled
Organization
without
Emergence
Controlled
Organization
with
Emergence
• ???
Looking for
Examples
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• ???
Looking for
Examples
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Some Readings on Emergence
Name
Year
Title
Fromm
Ten Questions about Emergence
Halley & Winkler
Classification of Emergence and its relation to self-organization
Batty
2003
The Emergence of Cities: Complexity and Urban Dynamics
Bar-Yam
A Mathematical Theory of Strong Emergence Using Multiscale Variety
Fromm
Types and Forms of Emergence
Corning
2002
The Re-Emergence of “Emergence”: A Venerable Concept in Search of a Theory
Bedau
Weak Emergence
Bedau
Downward Causation and the Autonomy of Weak Emergence
David & Courdier
See Emergence as a Metaknowledge
Ryan
2006
Emergence is Coupled to Scope, not Level
Osberg, Biesta & Cilliers
From Representation to Emergence: Complexity’s Challenge to the Epistemology
of Schooling
Osberg & Biesta
Complexity, Knowledge and the Incalculable: Epistemological and Preagogical
Implications of ‘Strong Emergence’
Scheffer & E.H. van NEss
Self-organized similarity, the evolutionary emergence of groups of similar species
Deguet, Demazeau & Magnin
Elements About the Emergence Issue: A Survey of Emergence Definitions
Dessales & Phan
Emergence in Multi-Agent Systems: Cognitive Hierarchy, Detection, and
Complexity Reduction. Part I: Methodological Issues
Abbott
Emergence Explained
Abbott
Emergence, Entities, Entropy and Binding Forces
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Source
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Complexity 7(6): 18-30
Ten Questions
(definitions 1-3, requirements 4-5, calculus 6-9, limitations 10)
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Can we Understand It? Can we Define a Comprehensive Taxonomy or Classification
What are the Underlying Principles? How are They Related? Is Novelty or the Need for
an Observer Among Them?
What is the Relation between Emergence and Evolution? Are there any processes
similar or related to “emergence” in evolution?
Are there any necessary requirements for “emergence” like mobility, intelligence or
suitable environments? Is emergence a typical property of MAS?
Is “emergence” only possible with simple or stupid agents? Or is it also possible
complex BDI agents?
Can we Find a Kind of Calculus for Multi-Agent Systems?
How Can a Globally Desired Structure or Functionality be Designed on the Basis of
Interactions Between Many Simple Modules? Can we solve the micro-macro link
problem?
Can We Use it? Is “emergence” one reason why agents are not widely used or why
agents could be a new successful “programming paradigm”
Can we Control it? Even if “emergence” is not predictable, is it in some ways
controllable?
What are the limitations of emergence and self-organization? (size limit, place limit,
complexity limit, combinatorial limit)
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Common Characteristics
• Radical Novelty (features not previously observed
in systems)
• Coherence or Correlation (meaning integrated
wholes that maintain themselves over some
period of time)
• A Global or Macro “Level” (there is some
property of wholeness)
• Product of a Dynamical Process (it evolves)
• Ostensive (it can be perceived)
• Supervenience – downward causation
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Emergent Properties & Processes
• An emergent behavior or emergent property can
appear when a number of simple entities (agents)
operate in an environment, forming more
complex behaviors as a collective.
• If emergence happens over disparate size scales,
then the reason is usually a causal relation across
different scales (in other words, there is a form of
top-down feedback in systems with emergent
properties).
• Etc.
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Emergent Structures
• Emergent structures are patterns not created
by a single event or rule. Nothing commands
the system to form a pattern.
• The emergent structures are more than the
sum of their parts because the emergent
order will not arise is the various parts are
simply co-existing; the interaction of these
parts is central.
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Three Forms of Emergent Structures
• First-Order emergent structures occur as a result of
shape interactions (e.g., hydrogen bonds in water
molecules lead to surface tension)
• Second-Order emergent structures involve shape
interactions played out sequentially over time (e.g.,
changing atmospheric conditions as a snowflake falls to
the ground build upon and alter its form)
• Third-Order emergent structures are a consequence of
shape, time, and heritable instructions (e.g., an
organism’s genetic code sets boundary conditions on
the interaction of biological systems in space and time)
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Weak and Strong Emergence
Weak Emergence
• Describes new properties
arising in systems as a result
of interactions at an
elemental level
• Weak: complex adaptive
behavior – simple rules
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Strong Emergence
• But, if systems have qualities that
are not directly traceable to the
system’s components, but rather
to how those components
interact, and one is willing to
accept that a system
SUPERVENES on its components,
then it if difficult to account for
an emergent property’s cause.
The new qualities are irreducible
to its constituent parts. The
whole is greater than the sum of
its parts. This view is called
strong emergence.
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Strong Emergence
Rare
Not Predictable in Principle
New or Many Systems
Boundary between Different Evolutionary
Systems, “barrier of relevance”
Gateway or Quantum Leap in Evolution to
New (Evolutionary) System
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Complexity v. Traditional Economics (Santa Fe Institute)
Dynamic
Agents
Networks
Emergence
Evolution
Technology
Complexity Economics
Open, dynamic, non-linear systems, far from
equilibrium
Modelled individually; use inductive rules of
thumb to make decisions; have incomplete
information; are subject to errors and biases; learn
to adapt over time; heterogeneous agents
Traditional Economics
Closed, static, lienar systems in equilibrium
Modelled collectively; use complex deductive
calculations to make decisions; have complete
information; make no errors and have no biases;
have no need for learning or adaptation (are
already perfect), mostly homogeneous agents
Explicitly model bi-lateral interactions between
Assume agents only interact indirectly through
individual agents; networks of relationships change market mechanims (e.g., auctions)
over time.
No distinction between micro/macro economics;
Micro- and macroeconomics remain separate
macro patterns are emergent result of micro level disciplines
behavior and interactions
The evolutionary process of differentiation,
No mechanism for endogenously creating novelty,
selection and amplification provide the system with or growth in order or complexity
novelty and is responsible for its growth in order
and complexity
Technology fluid, endogenous to the system
Technology as given or selected on economic basis
Preferences
Formulation of preferences becomes central;
individuals not necessarily selfish
Preferences given; Individuals selfish
Origins
Based on Biology (structure, pattern, selforganized, life cycle)
Based on 19th century Physics (equilibrium,
stability, deterministic dynamics)
Elements
Patterns and Possibilities
Price and Quantity
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Next
Results
Some Pictures /
Charts of Emerged
Pattern
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Some Thoughts
• From Weak
Emergence
• From Strong
Emergence
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Outline of Thought Process
• The System is Territorially Closed, but
Functionally Open
• The Emergent Pattern is calculable and
describable
• The key is to discover the “agents” that selforganized or the processes that self-organized
to RESULT in the emerged functional/spatial
pattern.
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40% Employment in
Specialized Centers
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A First Explanation
Elements of Weak Emergence
• The Shopping Center Model
– Places grew bigger and more
complex
• Places Change Their
Functionality in terms of
new pressures
– Historic centers become
functionally specialized
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Elements of Strong Emergence
• Global Business Districts
– The need for a new kind of
space for a new kind of
business
• Airport Related Development
– Fifth wave of transport
• Megaprojects? Planned
Decentralization? Istanbul
Examples.
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Next
Conclusions …
Regarding Regarding Regarding
Case Study Emergence Complexity
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… regarding the case study
• The pattern of centers has evolved (Marshall) over time
due to:
– Accident (which ones)
– Purposeful Decentralization of Office Functions (particularly
those involving IT) in the 1970s
– Positive Feedback: Purposeful Concentration of Functions
(particularly in the shipping/importing & exporting) functions) in
the 2000s
– Positive Feedback: Purposeful Concentration of Functions
(advanced producer services, particularly banking) in the 1990s
– Positive Feedback: Purposeful Concentration of Functions (eds,
meds, and govs)
– If US had historic centers, they might also evolve as specialized
tourist attractions
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… regarding emergence
• Still like it,
• Particularly in nested hierarchies
• Like the notion of slaving, strong attractors, some
endogenous guidance
• The really big planning idea is that endogenous
guidance factors are not always the things that political
systems or planners seek to guide or vice versa
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… regarding complexity
• The need to stay focused on substance – really
like the word “entities” in the physics and
philosophy literatures
• Let’s work on differentiating the words
“behavior” “pattern” “structure” etc
• Less is More –there is a set of universal …
West?!?!?!
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With all due respect to the planning theorists (Healey, Innes, et al.)
Tesekkür ederim, Danke, Gracias, Merci
for your UNDIVIDED (non-complex) attention
Emergence
(complexity theory)
as meta_knowledge
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We need Better Grammar
3rd Turn:
Return to
Content
Brain fried!
Time for Coffee!