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Agent-Based Models and Complexity Science in the Age of Geospatial Big Data pp 45–58Cite as

An Agent-Based Model to Identify Migration Pathways of Refugees: The Case of Syria

Part of the Advances in Geographic Information Science book series (AGIS)

Abstract

The Syrian civil war has generated a refugee crisis in the Middle East and Europe. This study draws on complex systems theory and the agent-based modelling method to simulate the movement of refugees in order to identify pathways of forced migration under the present crisis. The model generates refugees as agents and lets them leave conflict areas for a destination that they choose based on their respective characteristics and desires. The simulation outputs are compared with existing data regarding the state of forced migrations of Syrians to assess the performance of the model.

Keywords

  • Conflict induced migration
  • Syrian refugees
  • Agent-based modeling
  • GIS
  • Migration pathways

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Acknowledgments

Thanks to Dr. Anthony Jjumba for his valuable feedback and editing of this chapter.

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Authors and Affiliations

  1. Laboratoire de Géosimulation Environnementale, Department of Geography, Université de Montréal, Pavillon 520 Côte-Sainte-Catherine, Montréal, QC, Canada, H3T 1J4

    Guillaume Arnoux Hébert, Liliana Perez & Saeed Harati

Authors
  1. Guillaume Arnoux Hébert
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  2. Liliana Perez
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  3. Saeed Harati
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Corresponding author

Correspondence to Liliana Perez .

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Editors and Affiliations

  1. Laboratoire de Géosimulation Environnementale, Department of Geography, Université de Montréal, Montreal, Québec, Canada

    Liliana Perez

  2. Department of Geography, Pennsylvania State University, University Park, Pennsylvania, USA

    Eun-Kyeong Kim

  3. Department of Geography, School of Environment, McGill University, Montreal, Québec, Canada

    Raja Sengupta

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Hébert, G.A., Perez, L., Harati, S. (2018). An Agent-Based Model to Identify Migration Pathways of Refugees: The Case of Syria. In: Perez, L., Kim, EK., Sengupta, R. (eds) Agent-Based Models and Complexity Science in the Age of Geospatial Big Data. Advances in Geographic Information Science. Springer, Cham. https://doi.org/10.1007/978-3-319-65993-0_4

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