Skip to main content

Teaching the Complexity of Urban Systems with Participatory Social Simulation

  • Conference paper
  • First Online:
Advances in Social Simulation

Part of the book series: Springer Proceedings in Complexity ((SPCOM))

  • 907 Accesses

Abstract

We describe how we use social simulation as a core method in a new master’s program designed to teach future leaders of urban change to deal with the complexity inherent in current societal transformations. We start by depicting the challenges with regard to cross-disciplinary knowledge integration and overcoming value-based, rigid thinking styles that inevitably arise in the process of solving ecological, technological, or social problems in cities new and old. Next, we describe a course based on urban modeling and participatory approaches, designed to meet those challenges. We reflect on our first experience with this approach and discuss future developments and research needs.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 229.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 299.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 299.99
Price excludes VAT (USA)
  • Durable hardcover 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

Institutional subscriptions

References

  1. UN-Habitat (United Nations Human Settlement Programme). World Cities Report 2016. Urbanization and Development: Emerging Futures (2016). https://unhabitat.org/books/world-cities-report/

  2. Batty, M.: The New Science of Cities. MIT Press, Cambridge, MA (2013)

    Book  Google Scholar 

  3. Wilson, A.G.: Complex Spatial Systems: The Modelling Foundations of Urban and Regional Analysis. Pearson Education, Harlow (2000)

    Google Scholar 

  4. Crooks, A.T., Malleson, N., Wise, S., Heppenstall, A.: Big data, agents and the city. In: Schintler, L.A., Chen, Z. (eds.) Big Data for Urban and Regional Science, pp. 204–213. Routledge, New York (2018)

    Google Scholar 

  5. Burdett, R., Sudjic, D.: The Endless City. Phaidon, London (2006)

    Google Scholar 

  6. Prytula, M., Schröder, T., Dörk, M., Ortgiese, M., Michel, A., Neuroth, H., Lehmann, J.: Transformation lernen: Der Masterstudiengang Urbane Zukunft an der Fachhochschule Potsdam. Transform. Cities. 3, 76–79 (2016)

    Google Scholar 

  7. Ihde, D.: Models, Models Everywhere. In: Lenhard, J., Küppers, G., Shinn, T. (eds.) Simulation. Sociology of the Sciences Yearbook, vol. 2, pp. 79–86. Springer, Dordrecht (2006). https://doi.org/10.1007/1-4020-5375-4_5

    Chapter  Google Scholar 

  8. Epstein, J.M.: Why model? J. Artif. Soc. Soc. Simul. 11(4), 12 (2008). http://jasss.soc.surrey.ac.uk/11/4/12.html

    Google Scholar 

  9. Tetlock, P.E., Gardner, D.: Superforecasting: The Art and Science of Prediction. Random House, London (2015)

    Google Scholar 

  10. Pinker, S.: Enlightenment Now: The Case for Reason, Science, Humanism, and Progress. Penguin, London (2018)

    Google Scholar 

  11. Miller, G.: Roots of the urban mind. Science. 352(6288), 908–911 (2016). https://doi.org/10.1126/science.352.6288.908

    Article  Google Scholar 

  12. Rittel, H.W.J., Webber, M.M.: Dilemmas in a general theory of planning. Policy. Sci. 4, 155–169 (1973). https://doi.org/10.1007/BF01405730

    Article  Google Scholar 

  13. Schneidewind, U.: Transformative Wissenschaft-Motor für gute Wissenschaft und lebendige Demokratie. GAIA-Ecol. Perspect. Sci. Soc. 24(2), 88–91 (2015). https://doi.org/10.14512/gaia.24.2.5

    Article  Google Scholar 

  14. Mieg, H.A., Lehmann, J.: Forschendes Lernen: Wie die Lehre in Universität und Fachhochschule erneuert werden kann. Campus-Verlag, Frankfurt (Main) (2017)

    Google Scholar 

  15. Scholz, R.W., Lang, D.J., Wiek, A., Walter, A.I., Stauffacher, M.: Transdisciplinary case studies as a means of sustainability learning: historical framework and theory. Int. J. Sustain. High. Educ. 7(3), 226–251 (2006). https://doi.org/10.1108/14676370610677829

    Article  Google Scholar 

  16. Priebe, M., Szczepanska, T., Schröder, T., Prytula, M., Dörk, M.: Potentiale partizipativer Systemmodellierung in Brandenburger Kommunen. IaF Working Paper (2017). https://www.fh-potsdam.de/fileadmin/user_dateien/5_forschen/Publikationen/201711_Arbeitspapier_Pasymo.pdf

  17. Batty, M.: Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals. MIT Press, Cambridge (2005)

    Google Scholar 

  18. Iltanen, S.: Cellular automata in urban spatial modeling. In: Heppenstall, A.J., Crooks, A.T., See, L.M., Batty, M. (eds.) Agent-Based Models of Geographical Systems, pp. 69–84. Springer, Dordrecht (2012). https://doi.org/10.1007/978-90-481-8927-4_4

    Chapter  Google Scholar 

  19. Batty, M., Xie, Y., Sun, Z.: Modeling urban dynamics through GIS-based cellular automata. Comput. Environ. Urban. Syst. 233, 205–233 (1999). https://doi.org/10.1016/S0198-9715(99)00015-0

    Article  Google Scholar 

  20. White, R., Engelen, G.: Cellular-automata and fractal urban form - a cellular modeling approach to the evolution of urban land-use patterns. Environ. Plan. A. 25(8), 1175–1199 (1993). https://doi.org/10.1068/a251175

    Article  Google Scholar 

  21. Benenson, I., Torrens, P.M.: Geosimulation: Automata-Based Modeling of Urban Phenomena. Wiley, London (2004). https://doi.org/10.1002/0470020997

    Book  Google Scholar 

  22. Batty, M., Crooks, A.T., See, L.M., Heppenstall, A.J.: Perspectives on agent-based models and geographical systems. In: Heppenstall, A.J., Crooks, A.T., See, L.M., Batty, M. (eds.) Agent-Based Models of Geographical Systems, pp. 1–15. Springer, Dordrecht (2012). https://doi.org/10.1007/978-90-481-8927-4

    Chapter  Google Scholar 

  23. Felsen, M., Wilensky, U.: NetLogo Urban Suite – Sprawl Effect Model. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston (2007). http://ccl.northwestern.edu/netlogo/models/UrbanSuite-SprawlEffect

    Google Scholar 

  24. O’Sullivan, D., Millington, J., Perry, G., Wainwright, J.: Agent-based models – because they’re worth it? In: Heppenstall, A., Crooks, A., See, L., Batty, M. (eds.) Agent-Based Models of Geographical Systems, pp. 109–123. Springer, Dordrecht (2012). https://doi.org/10.1007/978-90-481-8927-4_6

    Chapter  Google Scholar 

  25. Taillandier, P., Vo, D.A., Amouroux, E., Drogoul, A.: GAMA: a simulation platform that integrates geographical information data, agent-based modeling and multi-scale control. In: Desai, N., Liu, A., Winikoff, M. (eds.) Principles and Practice of Multi-Agent Systems. PRIMA 2010. Lecture Notes in Computer Science, vol. 7057, pp. 242–258. Springer, Berlin, Heidelberg (2012). https://doi.org/10.1007/978-3-642-25920-3_17

    Chapter  Google Scholar 

  26. Miller, J.H., Page, S.E.: Complex Adaptive Systems: An Introduction to Computational Models of Social Life. Princeton University Press, Princeton (2007)

    MATH  Google Scholar 

  27. Grimm, V., Polhill, G., Touza, J.: Documenting social simulation models: the ODD protocol as a standard. In: Edmonds, B., Meyer, R. (eds.) Simulating Social Complexity. Understanding Complex Systems, pp. 117–133. Springer, Berlin, Heidelberg (2013). https://doi.org/10.1007/978-3-540-93813-2_7

    Chapter  Google Scholar 

  28. Edmonds, B., Meyer, R.: Simulating Social Complexity: A Handbook. Springer, Berlin, Heidelberg (2013). https://doi.org/10.1007/978-3-540-93813-2

    Book  MATH  Google Scholar 

  29. Crooks, A.T., Heppenstall, A.J.: Introduction to agent-based modeling. In: Heppenstall, A.J., Crooks, A.T., See, L.M., Batty, M. (eds.) Agent-Based Models of Geographical Systems, pp. 85–105. Springer, Dordrecht (2012). https://doi.org/10.1007/978-90-481-8927-4_5

    Chapter  Google Scholar 

  30. Wilensky, U., Rand, W.: An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo. MIT Press, Cambridge (2015)

    Google Scholar 

  31. Schelling, T.: Micromotives and Macrobehavior. W. W. Norton, London & New York (1978)

    Google Scholar 

  32. Axelrod, R.: The dissemination of culture, a model with local convergence and global polarization. J. Confl. Resolut. 41, 203–226 (1997). https://doi.org/10.1177/0022002797041002001

    Article  Google Scholar 

  33. Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S., Huse, G., Huth, A., Jepsen, J.U., Jørgensen, C., Mooij, W.M., Müller, B., Peer, G., Piou, C., Railsback, S.F., Robbins, A.M., Robbins, M.M., Rossmanith, E., Rüger, N., Strand, E., Souissi, S., Stillman, R.A., Vabø, R., Visser, U., DeAngelis, D.L.: A standard protocol for describing individual-based and agent-based models. Ecol. Model. 198, 115–126 (2006). https://doi.org/10.1016/j.ecolmodel.2006.04.023

    Article  Google Scholar 

  34. Grimm, V., Berger, U., DeAngelis, D.L., Polhill, G., Giske, J., Railsback, S.F.: The ODD protocol: a review and first update. Ecol. Model. 221, 2760–2768 (2010). https://doi.org/10.1016/j.ecolmodel.2010.08.019

    Article  Google Scholar 

  35. Vennix, J.: Group Model Building: Facilitating Team Learning Using System Dynamics. Wiley, New York (1996)

    Google Scholar 

  36. Etienne, M.: Companion Modelling: A Participatory Approach to Support Sustainable Development. Springer, Dordrecht (2014). https://doi.org/10.1007/978-94-017-8557-0

    Book  Google Scholar 

  37. Williams, R.A.: Lessons learned on development and application of agent-based models of complex dynamical systems. Simul. Model. Pract. Theory. 83, 201–212 (2017). https://doi.org/10.1016/j.simpat.2017.11.001

    Article  Google Scholar 

  38. Verhagen, H., Johansson, M., Jager, W.: Games and online research methods. In: Fielding, N., Lee, R., Blank, G. (eds.) The SAGE Handbook of Online Research Methods, 2nd edn. SAGE Publications Inc., London (2017). https://doi.org/10.4135/9781473957992.n17

    Chapter  Google Scholar 

  39. Gugerell, K., Zuidema, C.: Gaming for the energy transition. Experimenting and learning in co-designing a serious game prototype. J. Clean. Prod. 169, 105–116 (2017). https://doi.org/10.1016/j.jclepro.2017.04.142

    Article  Google Scholar 

Download references

Acknowledgments

We acknowledge funding from the European Funds for Regional Development, grant number 85009319.

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Szczepanska, T., Priebe, M., Schröder, T. (2020). Teaching the Complexity of Urban Systems with Participatory Social Simulation. In: Verhagen, H., Borit, M., Bravo, G., Wijermans, N. (eds) Advances in Social Simulation. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-34127-5_43

Download citation

Publish with us

Policies and ethics