2011
DOI: 10.1016/j.compenvurbsys.2010.06.001
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Multi-agent simulator for urban segregation (MASUS): A tool to explore alternatives for promoting inclusive cities

Abstract: a b s t r a c tUrban segregation represents a significant barrier to achieving social inclusion in cities. To mitigate this problem, it is necessary to implement policies founded upon a better understanding of segregation dynamics. This paper proposes MASUS, a multi-agent simulator for urban segregation, which provides a virtual laboratory for exploring the impacts of different contextual mechanisms on the emergence of segregation patterns. We illustrate the potential of MASUS through three experiments on segr… Show more

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Cited by 62 publications
(29 citation statements)
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“…Multi-agent technology is an effective new method of solving multidisciplinary, distributed and collaborative land-use planning decisions (Kurihara et al, 2005). Combining the MALPDSS system designed by the multi-agent method can support distributed collaborative group activities relatively well, improve the efficiency of user planning decisions and effectively enhance land use structure optimization and support decision capabilities (Feitosa et al, 2011). Fang (2011 constructed an urban industrial layout decision support system, which provided full technical support and information services to achieve the standardized management of urban industrial upgrading and optimization in China and to allow city, county and township governments to coordinate and regulate industry selection, investment, distribution and management.…”
Section: Optimal Decision Support Systems For Interactive Coupling Bementioning
confidence: 99%
“…Multi-agent technology is an effective new method of solving multidisciplinary, distributed and collaborative land-use planning decisions (Kurihara et al, 2005). Combining the MALPDSS system designed by the multi-agent method can support distributed collaborative group activities relatively well, improve the efficiency of user planning decisions and effectively enhance land use structure optimization and support decision capabilities (Feitosa et al, 2011). Fang (2011 constructed an urban industrial layout decision support system, which provided full technical support and information services to achieve the standardized management of urban industrial upgrading and optimization in China and to allow city, county and township governments to coordinate and regulate industry selection, investment, distribution and management.…”
Section: Optimal Decision Support Systems For Interactive Coupling Bementioning
confidence: 99%
“…City planners and decision makers should implement policies that minimize the possibility of segregation based on income, ethnical, gender, age, etc. Feitosa, Le, and Vlek (:104) define income segregation as “separation among the residential locations of different income groups.” These authors show that income segregation has a negative impact on urban populations by contributing to the social exclusion of disadvantaged groups. Poor people, living in the same areas or neighborhoods, are often associated with little quality of built and natural environments, higher exposure to violence and diseases (e.g., Sabatini, Caceres, and Cerda ; Torres et al ), and less societal participation, thus reducing their opportunities for jobs and skill improvement (e.g., Briggs ; Torres ).…”
Section: The Importance Of Cities' Resourcesmentioning
confidence: 99%
“…While water supply and sewage drainage systems exist across the entire territory (though not all homes are necessarily connected to them), public transport, street lighting and tree planting are grossly lacking in poor neighborhoods. Echoing the analyzes of different authors, Feitosa et al (2011) point out that several factors contribute to urban spatial segregation, including the job market and its socio-economic impact (salary level, job insecurity, etc.) and increasing poverty among poor workers and sub-standard living conditions.…”
Section: Economic Growth and Social Changes In Monte Claros: The Vertmentioning
confidence: 99%