Skip to main content
SpringerLink
Log in
Book cover

International Workshop on Agent Based Modelling of Urban Systems

ABMUS 2016: Agent Based Modelling of Urban Systems pp 3–20Cite as

Towards an Agent-Based Simulation of Housing in Urban Beirut

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10051))

Abstract

Advances in agent-based modelling have led to theoretically-grounded spatial agent models of urban dynamics, capturing the dynamics of population, property prices, and regeneration. We leverage our extant agent-based model founded on the rent-gap theory, as a lens to study the effect of sizeable refugee migration in an abstracted model of a densely-populated Mediterranean city. Our exploratory work provides the foundation for calibration with real data, and offers a step towards a tool for policy makers asking what-if questions about the urban environment in the context of migration.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    Experiments show that larger abstract grid sizes yield the same observed dynamics, considering also that all the parameters are held proportional.

  2. 2.

    We do not consider other refugee populations, including those of Palestinian origin.

References

  1. Axelrod, R.: The dissemination of culture: a model with local convergence and global polarization. J. Conflict Resolut. 41(2), 203–226 (1997)

    Article  Google Scholar 

  2. Benenson, I.: Multi-agent simulations of residential dynamics in the city. Comput. Environ. Urban Syst. 22(1), 25–42 (1998)

    Article  Google Scholar 

  3. Bourassa, S.: The rent gap debunked. Urban Stud. 30(10), 1731–1744 (1993)

    Article  Google Scholar 

  4. CIA World Factbook: Lebanon (2016). https://www.cia.gov/library/publications/the-world-factbook/geos/le.html

  5. Diappi, L., Bolchi, P.: Gentrification waves in the inner-city of Milan: a multi agent/cellular automata model based on Smith’s rent gap theory. In: Innovations in Design & Decision Support Systems in Architecture and Urban Planning, pp. 187–201. Springer, Berlin (2006)

    Google Scholar 

  6. Diappi, L., Bolchi, P.: Smith’s rent gap theory and local real estate dynamics: a multi-agent model. Comput. Environ. Urban Syst. 32(1), 6–18 (2008)

    Article  Google Scholar 

  7. Fawaz, M., Sabah, M.: Charting a path: opening the path to affordable middle income housing. Executive Mag., 18 June 2015. http://www.executive-magazine.com/opinion/comment/charting-a-path

  8. Feitosa, F.F., Le, Q.B., Vlek, P.L.: Multi-agent simulator for urban segregation (MASUS): a tool to explore alternatives for promoting inclusive cities. Comput. Environ. Urban Syst. 35(2), 104–115 (2011)

    Article  Google Scholar 

  9. Fuentes-Fernández, R., Galán, J.M., Hassan, S., López-Paredes, A., Pavón, J.: Application of model driven techniques for agent-based simulation. In: Demazeau, Y., Dignum, F., Corchado, J.M., Pérez, J.B. (eds.) Advances in Practical Applications of Agents and Multiagent Systems. AISC, vol. 70, pp. 81–90. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  10. Ge, J.: Who creates housing bubbles? An agent-based study. In: Alam, S.J., Parunak, H.V.D. (eds.) MABS 2013. LNCS (LNAI), vol. 8235, pp. 143–150. Springer, Heidelberg (2014). doi:10.1007/978-3-642-54783-6_10

    Chapter  Google Scholar 

  11. Giffinger, R., Seidl, R.: Micro-modelling of gentrification: a useful tool for planning? In: Modeling and Simulating Urban Processes, pp. 59–76. LIT Verlang (2013). Chap. 3

    Google Scholar 

  12. Harvey, D.: Rebel Cities: From the Right to the City to the Urban Revolution. Verso Books, London (2012)

    Google Scholar 

  13. Huang, Q., Parker, D.C., Filatova, T., Sun, S.: A review of urban residential choice models using agent-based modeling. Environ. Planning B Planning Des. 40, 1–29 (2014)

    Google Scholar 

  14. Kravari, K., Bassiliades, N.: A survey of agent platforms. J. Artif. Soc. Soc. Simul. 18(1), 11 (2015)

    Google Scholar 

  15. Krijnen, M., Fawaz, M.: Exception as the rule: high-end developments in Neoliberal Beirut. Built Environ. 36, 245–259 (2010)

    Article  Google Scholar 

  16. Lebanese Information Center: The Lebanese demographic reality (2013). http://www.lstatic.org/PDF/demographenglish.pdf

  17. Magee, L.: Simulating a ‘Fierce Planet’: a web-based agent platform and sustainability game. In: Proceedings of 2012 Spring Simulation Multiconference (SpringSim 2012) (2012)

    Google Scholar 

  18. North, M.J., Macal, C.M.: Managing Business Complexity: Discovering Strategic Solutions with Agent-based Modeling and Simulation. OUP, New York (2007)

    Book  Google Scholar 

  19. O’Sullivan, D.: Toward micro-scale spatial modeling of gentrification. J. Geogr. Syst. 4(3), 251–274 (2002)

    Article  Google Scholar 

  20. Patel, A., Crooks, A., Koizumi, N.: Slumulation: an agent-based modeling approach to slum formations. J. Artif. Soc. Soc. Simul. 15(4), 2 (2012)

    Google Scholar 

  21. Picascia, S.: A theory driven, spatially explicit agent-based simulation to model the economic and social implications of urban regeneration. In: Proceedings of the 11th Conference of the European Social Simulation Association (ESSA 2015) (2015)

    Google Scholar 

  22. Picascia, S., Edmonds, B., Heppenstall, A.: Agent based exploration of urban economic dynamics under the rent-gap hypotheses. In: Grimaldo, F., Norling, E. (eds.) MABS 2014. LNCS (LNAI), vol. 9002, pp. 213–227. Springer, Heidelberg (2015). doi:10.1007/978-3-319-14627-0_15

    Google Scholar 

  23. Portugali, J.: Toward a cognitive approach to urban dynamics. Environ. Planning B Planning Des. 31(4), 589–613 (2004)

    Article  Google Scholar 

  24. Portugali, J.: Revisiting cognitive dissonance and memes-derived urban simulation models. In: Portugali, J. (ed.) Complexity, Cognition and the City. Understanding Complex Systems, pp. 315–334. Springer, Heidelberg (2011). doi:10.1007/978-3-642-19451-1_17

  25. Schelling, T.C.: Dynamic models of segregation. J. Math. Sociol. 1(2), 143–186 (1971)

    Article  Google Scholar 

  26. Singh, D., Padgham, L.: OpenSim: a framework for integrating agent-based models and simulation components. In: Proceedings of 21st European Conference on Artificial Intelligence (ECAI 2014), pp. 837–842 (2014)

    Google Scholar 

  27. Smith, N.: Toward a theory of gentrification a back to the city movement by capital, not people. J. Am. Plann. Assoc. 45(4), 538–548 (1979)

    Article  Google Scholar 

  28. Smith, N.: The New Urban Frontier: Gentrification and the Revanchist City. Routledge, London (1996)

    Google Scholar 

  29. Srour, F.J., Yorke-Smith, N.: Towards agent-based simulation of maritime customs. In: Proceedings of 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2015), pp. 1637–1638 (2015)

    Google Scholar 

  30. Srour, F.J., Yorke-Smith, N.: Assessing maritime customs process re-engineering using agent-based simulation. In: Proceedings of 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), pp. 786–795 (2016)

    Google Scholar 

  31. Stanilov, K., Batty, M.: Exploring the historical determinants of urban growth patterns through cellular automata. Trans. GIS 15(3), 253–271 (2011)

    Article  Google Scholar 

  32. United Nations Development Programme: Poverty, growth and income distribution in Lebanon (2008). http://www.undp.org

  33. United Nations High Commissioner for Refugees: 2015 UNHCR country operations profile - Lebanon (2015). http://www.unhcr.org/pages/49e486676.html

  34. Wilensky, U.: NetLogo (1999). http://ccl.northwestern.edu/netlogo

  35. Zhang, H., Li, Y.: Agent-based simulation of the search behavior in China’s resale housing market: evidence from Beijing. J. Artif. Soc. Soc. Simul. 17(1), 18 (2014)

    Google Scholar 

Download references

Acknowledgments

We thank the anonymous reviewers of the ABMUS 2016 workshop for their constructive comments, and the participants at the workshop for discussions. We thank Joseph Bechara, Bruce Edmonds, Mona Fawaz, Alison Heppenstall, and Ali Termos. This work was partially funded by the University Research Board of the American University of Beirut under grant number 103183.

Author information

Authors and Affiliations

  1. Centre for Policy Modelling, Manchester Metropolitan University, Manchester, UK

    Stefano Picascia

  2. Laboratorio Dati Economici Storici Territoriali, University of Siena, Siena, Italy

    Stefano Picascia

  3. Olayan School of Business, American University of Beirut, Beirut, Lebanon

    Neil Yorke-Smith

Authors
  1. Stefano Picascia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Neil Yorke-Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Neil Yorke-Smith .

Editor information

Editors and Affiliations

  1. University of Wollongong , Wollongong, New South Wales, Australia

    Mohammad-Reza Namazi-Rad

  2. RMIT University , Melbourne, Victoria, Australia

    Lin Padgham

  3. University of Wollongong , Wollongong, New South Wales, Australia

    Pascal Perez

  4. Technische Universität Berlin , Berlin, Germany

    Kai Nagel

  5. Universidade Federal do Rio Grande do Sul , Rio Grande do Sul, Brazil

    Ana Bazzan

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Picascia, S., Yorke-Smith, N. (2017). Towards an Agent-Based Simulation of Housing in Urban Beirut. In: Namazi-Rad, MR., Padgham, L., Perez, P., Nagel, K., Bazzan, A. (eds) Agent Based Modelling of Urban Systems. ABMUS 2016. Lecture Notes in Computer Science(), vol 10051. Springer, Cham. https://doi.org/10.1007/978-3-319-51957-9_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-51957-9_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51956-2

  • Online ISBN: 978-3-319-51957-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation