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Multi-Agent Simulator for Multi-Agent Simulator for Urban Segregation (MASUS)Urban Segregation (MASUS)
A Tool to Explore Alternatives for A Tool to Explore Alternatives for Promoting Inclusive CitiesPromoting Inclusive Cities
Flávia da Fonseca Feitosa
Since 2008, the majority of the world’s population lives in urban Since 2008, the majority of the world’s population lives in urban areasareas
An Urban AgeAn Urban Age
Source: UN-Habitat, 2007
An Urban AgeAn Urban Age
Is this a problem? Is this a problem?
““Cities are not the problem; They Cities are not the problem; They are the solution!”are the solution!”
(Jaime Lerner) (Jaime Lerner)
Potential as engines of developmentPotential as engines of development
An Urban AgeAn Urban Age
Inclusive CitiesInclusive Cities
Promote growth with equity
A place where everyone can benefit from the opportunities cities offer
A barrier to the formation of inclusive A barrier to the formation of inclusive citiescities
Urban Urban SegregationSegregation
Obstacles that Obstacles that contribute to contribute to perpetuate perpetuate
povertypoverty
Impacts of Impacts of SegregationSegregation
Policies to minimize segregation Policies to minimize segregation demand:demand:
A better understanding of the A better understanding of the dynamics of segregation and its dynamics of segregation and its
causal mechanismscausal mechanisms
Segregation displays many of the hallmarks Segregation displays many of the hallmarks of complexityof complexity
Complex Nature of Complex Nature of SegregationSegregation
The Process Matters!The Process Matters!
Complex Nature of Complex Nature of SegregationSegregation
Require bottom-up simulations Agent-Based Model
Agent-Based Models (ABM)Agent-Based Models (ABM)
Focus on Focus on individual decision-making units individual decision-making units (agents), which interact with each other and (agents), which interact with each other and their environmenttheir environment
Natural way to explore the emergence of Natural way to explore the emergence of global structuresglobal structures
MMulti-ulti-AAgent gent SSimulator for imulator for UUrban rban SSegregationegregation
MASUSMASUS
Scientific tool to explore alternative scenarios of segregation
Support planning actions by offering insights about the impact of policy strategies
PurposePurpose
Improve the understanding about segregation and its relation with different contextual mechanisms
MASUS Conceptual MASUS Conceptual ModelModel
São José dos Campos, São José dos Campos, BrazilBrazil
São Paulo StateStudy Area
City of São José dos Campos
MASUS: Process MASUS: Process ScheduleSchedule
Decision-making sub-Decision-making sub-modelmodelALTERNATIVESALTERNATIVES• 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 Higher probability to choose alternative with higher utilitywith higher utility
Decision-making sub-Decision-making sub-modelmodel
Nesting Structure of the Nesting Structure of the ModelModel
MASUS: Process MASUS: Process ScheduleSchedule
Operational ModelOperational Model
Simulation Simulation ExperimentsExperiments
Comparing simulation outputs with Comparing simulation outputs with empirical dataempirical data
Testing theoretical issuesTesting theoretical issues
Testing anti-segregation policy Testing anti-segregation policy strategiesstrategies
Comparison with Empirical Comparison with Empirical DataData
Initial condition: São José dos Initial condition: São José dos Campos in 1991Campos in 1991• Import GIS layers (households, environment)Import GIS layers (households, environment)
• Set parametersSet parameters
Run 9 annual cyclesRun 9 annual cycles
Compare simulated results with real Compare simulated results with real data (year 2000)data (year 2000)
Comparison with Empirical Comparison with Empirical DataData
Dissimilarity Index (local scale)
Initial State (1991)
Simulated Data (1991-2000)
Real Data (2000)
0.54
0.310.15
0.51
0.300.19
0.51
0.300.19
Comparison with Empirical Comparison with Empirical DataData
Isolation Poor Households (local scale)
Initial State (1991)
Real Data (2000)
0.54 0.51 0.51
Simulated Data (1991-2000)
Comparison with Empirical Comparison with Empirical DataData
Isolation Affluent Households (local scale)
Initial State (1991)
Real Data (2000)
0.15 0.19 0.19
Simulated Data (1991-2000)
Testing a theoryTesting a theory
How does inequality affect How does inequality affect segregation? segregation?
Relation between both phenomena has caused controversy in scientific debates
Experiment Compare 3 scenarios 1991-2000
Scenario 1: Previous run (baseline)
Scenario 2: Decreasing inequality
Scenario 3: Increasing inequality
Testing a theoryTesting a theory
Inequality (Gini) Proportion Poor HH Proportion Affluent HH
Scenario 1 (Original) Scenario 2 (Low-Ineq.) Scenario 3 (High-Ineq.)
Dissimilarity Isolation Poor HH Isolation Affluent HH
Testing policy Testing policy strategiesstrategies
Experiment Compare 3 scenarios
Scenario 1 no voucher (baseline)
Scenario 2 200 – 1700 vouchers
Scenario 3 400 – 4200 vouchers
Poverty Dispersion vs. Wealth Poverty Dispersion vs. Wealth DispersionDispersion
Poverty Dispersion: housing vouchers to poor families
Testing policy Testing policy strategiesstrategies
Scenario 1 No voucher (baseline)
Scenario 2 200 - 1700 vouchers
(2.3%)
Scenario 3 400 - 4200 vouchers
(5.8%)
Dissimilarity Isolation Poor HH
Isolation Affluent HH
2.3 - 3.5 %5.8 - 10.7%
2.3 - 1.7 %5.8 - 3.4%
2.3 - 5.7 %5.8 - 8.3 %
Testing policy Testing policy strategiesstrategies
Poverty DispersionPoverty Dispersion
Demands high and continous investment Demands high and continous investment to decrease poverty isolationto decrease poverty isolation
Poverty Dispersion vs. Wealth Poverty Dispersion vs. Wealth DispersionDispersion
Slows down the increase in segregation, Slows down the increase in segregation, but does not change the trendsbut does not change the trends
ExperimentExperiment Compare 2 scenariosCompare 2 scenarios
Scenario 1 (baseline)
Scenario 2 new areas for upper classes
Urban areas in 1991Undeveloped areas for upper classes
Testing policy Testing policy strategiesstrategiesPoverty Dispersion vs. Wealth Poverty Dispersion vs. Wealth
DispersionDispersionWealth Dispersion: Wealth Dispersion: Incentives for constructing Incentives for constructing
residential developments for upper classes in poor residential developments for upper classes in poor regions of the cityregions of the city
Testing policy Testing policy strategiesstrategies
Scenario 1 baseline
Scenario 2 new areas for
upper classes
Dissimilarity Isolation Poor HH
Isolation Affluent HH
Testing policy Testing policy strategiesstrategies
Wealth DispersionWealth Dispersion
Produces long-term outcomesProduces long-term outcomes
Poverty Dispersion vs. Wealth Poverty Dispersion vs. Wealth DispersionDispersion
More effective at decreasing large-scale More effective at decreasing large-scale segregationsegregation
E.g. Dissimilarity 2010E.g. Dissimilarity 2010
local scale (700m): - 19%local scale (700m): - 19%
large scale (2000m): - 36%large scale (2000m): - 36%
Testing policy Testing policy strategiesstrategies
Wealth DispersionWealth Dispersion
Positive changes in the spatial patterns of Positive changes in the spatial patterns of segregationsegregation
Poverty Dispersion vs. Wealth Poverty Dispersion vs. Wealth DispersionDispersion
Baseline2010
Wealth Dispersion2010
Concluding RemarksConcluding Remarks
MASUS: MASUS: MMulti-ulti-AAgent gent SSimulator for imulator for UUrban rban SSegregationegregation
Virtual laboratory for testing theories and Virtual laboratory for testing theories and policy approaches on segregationpolicy approaches on segregationDoes Does notnot focus on making exact predictions focus on making exact predictions
Exploratory tool, framework for assembling Exploratory tool, framework for assembling relevant informationrelevant information
Oriented towards understanding and Oriented towards understanding and structuring debates in participative structuring debates in participative processes of decision supportprocesses of decision support
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