Multi-Agent Simulator for Urban Segregation (MASUS) A Tool to Explore Alternatives for Promoting Inclusive Cities

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Multi-Agent Simulator for Urban Segregation
(MASUS)A Tool to Explore Alternatives for
Promoting Inclusive Cities
Flávia da Fonseca Feitosa
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An Urban Age
Since 2008, the majority of the worlds
population lives in urban areas
Source UN-Habitat, 2007
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An Urban Age
Is this a problem?
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An Urban Age
Inclusive Cities
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Urban Segregation
A barrier to the formation of inclusive cities
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Impacts of Segregation
Obstacles that contribute to perpetuate poverty
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Complex Nature of Segregation
Segregation displays many of the hallmarks of
complexity
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Complex Nature of Segregation
The Process Matters!
Require bottom-up simulations ?
Agent-Based Model
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MASUS
Multi-Agent Simulator for Urban Segregation
Scientific tool to explore alternative scenarios
of segregation
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MASUS Conceptual Model
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São José dos Campos, Brazil
City of São José dos Campos
Study Area
São Paulo State
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MASUS Process Schedule
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Decision-making sub-model

• ALTERNATIVES
• Not Move
• Move within the same neighborhood
• Move to the same type of neighborhood (n
  alternatives)
• Move to a different type of neighborhood (m
  alternatives)
• Higher probability to choose alternative with
  higher utility

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Decision-making sub-model
Nesting Structure of the Model
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MASUS Process Schedule
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Operational Model
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Simulation Experiments
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Comparison with Empirical Data
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Comparison with Empirical Data
Dissimilarity Index (local scale)
Real Data (2000)
Initial State (1991)
Simulated Data (1991-2000)
0.54
0.51
0.31
0.30
0.15
0.19
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Comparison with Empirical Data
Isolation Poor Households (local scale)
Real Data (2000)
Initial State (1991)
Simulated Data (1991-2000)
0.54
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Comparison with Empirical Data
Isolation Affluent Households (local scale)
Real Data (2000)
Initial State (1991)
Simulated Data (1991-2000)
0.15
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Testing a theory
How does inequality affect segregation? Relation
between both phenomena has caused controversy in
scientific debates
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Testing a theory
Proportion Poor HH
Inequality (Gini)
Proportion Affluent HH
Scenario 1 (Original)
Scenario 2 (Low-Ineq.)
Scenario 3 (High-Ineq.)
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Testing policy strategies
Poverty Dispersion vs. Wealth Dispersion
Poverty Dispersion housing vouchers to poor
families
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Testing policy strategies
Isolation Poor HH
Dissimilarity
2.3 - 3.5 5.8 - 10.7
2.3 - 1.7 5.8 - 3.4

• Scenario 1
• No voucher (baseline)
• Scenario 2
• 200 - 1700 vouchers (2.3)
• Scenario 3
• 400 - 4200 vouchers (5.8)

Isolation Affluent HH
2.3 - 5.7 5.8 - 8.3
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Testing policy strategies
Poverty Dispersion Demands high and continous
investment to decrease poverty isolation
Poverty Dispersion vs. Wealth Dispersion
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Testing policy strategies
Poverty Dispersion vs. Wealth Dispersion

• Wealth Dispersion Incentives for constructing
  residential developments for upper classes in
  poor regions of the city

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Testing policy strategies
Isolation Poor HH
Dissimilarity
Isolation Affluent HH

• Scenario 1
• baseline
• Scenario 2
• new areas for upper classes

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Testing policy strategies
Wealth Dispersion Produces long-term outcomes
Poverty Dispersion vs. Wealth Dispersion
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Testing policy strategies
Wealth Dispersion Positive changes in the
spatial patterns of segregation
Poverty Dispersion vs. Wealth Dispersion
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Concluding Remarks
MASUS Multi-Agent Simulator for Urban
Segregation Virtual laboratory for testing
theories and policy approaches on segregation