1. `
Agent-Based Modeling for exploring
Pakistan’s Urban Dynamics
Ammar A. Malik
Hilton L. Root
Andrew T. Crooks
Melanie Swartz
SWARMFEST 2013
Orlando, FL
2. Presentation Outline
• Acknowledgement: IFPRI, Pakistan Planning Commission
• The Urban Century
• Role of Creativity in Urban Development
• The Creative City Model
• Experiments: Karachi
• The Next Steps
6. The Expansion of Cities
• World Urbanization: 50% in 2006, 75% by 2050.
• Every week, more than 1 million people are being added
to cities, likely to continue till 2050.
• Problems: global warming, pollution/disease, energy.
• Solutions: crucibles of civilization, avenues for
unleashing entrepreneurial energy.
8. Developing Country Megacities
Population Growth Comparison
0
2
4
6
8
10
12
14
16
18
1970 1980 1990 2000 2010
Millions
Cairo
Beijing
Jakarta
Delhi
Karachi
Source: United Nations
9. Why Karachi?
• The journey from being the ‘Beirut of South Asia’ to ‘the most
violent city on earth’
• “The world’s fastest growing megacity, has grown 80%
between 2000 and 2010 to 21m people” (Forbes 2013)
• A microcosm of Pakistan, representation of all ethnicities.
• Produces 20% of national GDP, 25% of national revenues,
handles 95% of foreign trade, retains 45% of employment in
large-scale manufacturing (ADB 2005)
• Pakistan’s financial and banking hub: hosts 40% of all
financial activity and 50% of bank deposits (KSDP 2007)
11. Insights from Literature
• Individual or Social?
• Creative ideas have “novelty, usefulness and surprise”
(Simonton 2012)
• Richard Florida’s (2002) “Theory of the Creative Class”
o Creative workers, who “draw on complex bodies of knowledge
to solve specific problems” associated with prosperity
o The 3Ts: Technology, Tolerance & Talent
• Human Capital driving long-term economic growth
(Barro 2001; Cohen and Soto 2007)
o Creative Clusters in cities are formed by free flow of ideas
(Andersson 1985)
12. New Urbanism
• Density fosters human interactions, “the loci for
development” (Glaeser 2011)
o Environmental Efficiency
o Education as the “most reliable predictor of urban growth”
o Successful cities attract the poor; they thrive on diversity
• Vibrant Urban Culture & Public Spaces (Landry 2000)
o Cultural and physical amenities attract creative individuals
• Jacobs (1961) “Cities happen to be problems in organized
complexity, like the life sciences.”
o “…the whole is more than the sum of the parts.” (Simon 1962)
o Understanding the macro-level from individual-level interaction
13. Model Purpose
• An Urban Laboratory for asking what if questions and testing
policy ideas.
• To Explain:
o The relationship between land-use regulation and creative economy.
o When, where and how creative clusters emerge in cities?
• To Test Policy Scenarios:
o What if land-use zones are altered in favor of mixed land-use?
o What if urban mobility or transportation costs change?
o What if income inequality across households improves?
15. The Creative City Model
• Conceptual model built using Netlogo
• Scope of model area representation is a city or urban area
• System behaviors:
o Impact attributes of and number of agents in model over time
o Restrict or enable where agents can interact with the environment
• Agent behaviors:
o Agents are dynamic and change over time
o Interact with other agents
o Interact with the environment
• Environment behaviors:
o Change over time
o Impacted by agents
17. Model Features and Attributes
Individual Agents
Assigned at the start.
When an agent is “inspired”
by partnering with a high
creative agent in a creative
space, the agent can raise a
level.
Creativity Level
High
Med
Low
Creative Space and Value
Based on frequency of
visits by medium and
high creative agents.
Or, based on creative-
density.
Environment
18. The Creative City Model Flow
elSet up environment
(landuse, neighborhoods,
creative space, rent)
Set up agents with attributes
(income, education, tolerance,
creativity)
Pop Growth
and Brain Drain
Partner/Inspir
e Creativity
via Interaction
Update
Environment
Values (Rent,
Creative Space)
Update displays and
check interface values
Content
and
Satisfied
?
Check
Satisfaction
Move
yes
no
stay
Update creative
value from
frequency visit
by med and
high creative
Adjust rents
If max creative
value, convert
neighbor cells
to creative
space
Creative
space?
Find partner
Get inspired?
Un couple
Is partner
medium or
high creative?
Is place high
creative
value?
Raise Creativity
Environment
(affordability,
occupancy,
landuse,
neighborhood)
Check
tolerance
level of
nearby
Start
Sim
End
Sim?
19. Behavioral Rules Summary
Role Behavioral Rule
Agent Movement
Stop when satisfied (based on environment) and
content (based on nearby agents)
Agent Interaction Partnering may lead to increased creativity level
Environment Values
(Density, Rent, Occupancy,
Creative Value)
Based on density/frequency of agent visit
User controls Impact range of movement of agents
User interaction
Modify values, change display of environment and
agents based on attributes, query agents
22. • Allowing development typically increases amount of creative space
• Restricting movement does not have as big an impact as anticipated
• Ability to afford rent in a desired neighborhood and tolerance of the
neighbors also have a large impact
Parameter Sweep Findings
0
2
4
6
8
10
12
14
0 10 20 30 40 50 60 70 80 90 100
CreativeSpace
Tolerance Level
Tolerance Level
12.6
12.65
12.7
12.75
12.8
12.85
12.9
12.95
13
13.05
13.1
0 25 50 75 100 200
CreativeSpace
Rent Percentage of Income
Rent Percentage of Income
23. 0
2
4
6
8
10
12
14
-10 -5 0 5 10 15
CreativeSpace
Brain Drain
Brain Drain
0
2
4
6
8
10
12
14
16
18
-10 -5 0 5 10
CreativeSpace
Population Growth Rate
Population Growth Rate
Parameter Sweep Findings
• Brain drain and population growth have a large impact on ability to
support creative spaces, more so than just size of population.
26. Karachi Experiments
Input Parameters Karachi Values*
Starting Population 1,800
Population Growth Rate 3
Education 50
Brain Drain 5
Percent Highly Creative 15
Tolerance 30
Income(average) / top10 30,000 / 100,000
Average Rent 12,000
Rent Percentage of Income 40
* Karachi values interpolated based on recent Pew Research Study
Experiments*
Movement ON/OFF
Development ON/OFF
Segregation ON/OFF
* Run model for period of 10 years for each combination
27. Business as usual…
Key Outputs Today 3 Years 5 Years 10 Years 20 Years
Percent
Highly Creative
10 7 6 3 1
Gini Coefficient 0.67 0.66 0.69 0.72 0.75
Percent
Creative Space
1.8 3.7 6 4.5 4.8
Percent
University Edu.
50 38 32 21 15
Average
Income (Rs.)
37,000 41,165 45,200 55,013 60,394
Percent
Affording Rent
46 45 44 43 45
28. Karachi Experiments Results
Segregation ON
Rest. Movement OFF
Development OFF
(Base)
Rest. Movement OFF
Development ON
Rest. Movement ON
Development OFF
Rest. Movement ON
Development ON
Percent
Creative Space
<1 <1 <1 <1
Percent Afford Rent 35 38 38 38
Percent
Creative Population
11.8 12 12 12
Segregation OFF
Percent
Creative Space
2 1 3 1
Percent Afford Rent 46 93 45 92
Percent
Creative Population
12.5 12 13.2 12
29. Karachi Findings
• Few creative clusters emerge, creative space is very low, as expected.
• Key issues for Karachi: high brain drain and low tolerance.
• Development, or mixed land-use, alone won’t work.
• Smart development strengthening neighborhoods and increasing
access to creative places fosters creativity.
• More experimentation, calibration & interpretation!
30. The Next Steps
• Apply verified theoretical model to Karachi.
• GIS Integration, using R for spatial economic data analysis.
• Empirically grounded behavioral rules, Karachi fieldwork.
• Applying Creative City Model to several real-world cities!
