The Multi-Agent Simulation of the Economic and Spatial Dynamics of a Poli-Nucleated Urban Area

  • Ferdinando Semboloni


A multi-agents simulation model for the development of a poli-nucleated urban area is presented. This model, CityDev, is based on agents, goods and markets. Each agent (family, industrial firm, commercial firm, service firm, or developer) produces goods (labor, buildings, consumption goods) by using other goods and exchanges the goods in the markets. Each agent needs a building where to live or work, hence the urban fabric is produced and transformed as the result of the co-evolution of the economic and spatial systems. The model is applied to Florence (Italy) and its main feature — the interactivity via Internet is shown. In fact web users can direct during the simulation the agents generated by the simulator as well as the new agents established by themselves. In conclusion the basic characteristics of a multiagents method are highlighted: the comprehensive character of an agent based simulation, the ability to interact with human users, and the validation based both on observed data and on a direct interaction with real actors.


Cellular Automaton Urban System Human User Industrial Firm Urban Fabric 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Arentze T, Borgers A, Timmermans H (2000) A knowledge-based system for developing etail location strategies. Computers, Environment and Urban Systems 24: 489–508CrossRefGoogle Scholar
  2. Arentze T, Timmermans H (2003) A multiagent model of negotiation processes between ultiple actors in urban developments: a framework for and results of numerical experiments. Environment and Planning B: Planning and Design 30: 391–410CrossRefGoogle Scholar
  3. Batty M (2003) Agents, cells and cities: New representational models for simulating multiscale urban dynamics. CASA, Working Paper nr. 65, University College London, UKGoogle Scholar
  4. Benenson I (1998) Multi-agent simulations of residential dynamics in the city. Computers, Environments and Urban Systems 22: 25–42CrossRefGoogle Scholar
  5. Benenson I, Torrens PM (2004) Geosimulation: Automata-based modeling of urban phenomena. Wiley, New YorkGoogle Scholar
  6. Duffy J (2001) Learning to speculate: Experiments with artificial and real agents. Journal of Economic Dynamics and Control 25: 295–319CrossRefGoogle Scholar
  7. Epstein ME, Axtell R (1996) Growing Artificial Societies-Social Science from the Bottom Up. MIT Press, Cambridge, MAGoogle Scholar
  8. Ettema D, de Jong K, Timmermans H, Bakema A (2005) PUMA: multi agent modelling of urban systems. In 45th Congress of the European Regional Science Association, Vrije Universiteit, AmsterdamGoogle Scholar
  9. Lee DB (1973) Requiem for large scale urban models. Journal of the American Institute of Planners 39:3: 163–178Google Scholar
  10. Li X, Yeh AGO (2002) Neural-network-based cellular automata for simulating multiple land use changes using GIS. International Journal of Geographical Information Science 16: 323–343CrossRefGoogle Scholar
  11. Ligtenberga A, Wachowicza M, Bregta AK, Kettenisb ABDL (2004) A design and application of a multi-agent system for simulation of multi-actor spatial planning. Journal of Environmental Management 72: 43–55CrossRefGoogle Scholar
  12. Miller EJ, Hunt JD, Abraham JE, Salvini PA (2004) Microsimulating urban systems. Computers, Environment and Urban Systems 28: 9–44CrossRefGoogle Scholar
  13. Nagel K, Schreckenberg M (1992) Cellular automaton model for freeway traffic. J. Physique I 2: 2221CrossRefGoogle Scholar
  14. O’Sullivan D (2002) Toward micro-scale spatial modeling of gentrification. Journal of Geographical Systems 4: 251–274CrossRefGoogle Scholar
  15. Otter HS, van der Veen A, de Vriend HJ (2001) ABLOoM: Location behaviour, spatial patterns, and agent-based modelling. Journal of Artificial Societies and Social Simulation 4 Google Scholar
  16. Parker DC, Manson SM, Janssen MA (2003) Multi-agent systems for the simulation of land-use and land-cover change: A review. Annals of the Association of American Geographers 93: 314–337CrossRefGoogle Scholar
  17. Portugali J, Benenson I (1995) Artificial planning experience by means of an heuristic cellspace model: simulating international migration in the urban process. Environment and Planning A 27: 1647–1665CrossRefGoogle Scholar
  18. Schelhorn T, O’Sullivan D, Haklay M, Thurstain-Goodwin M (1999) Strests: An agent based pedestrian model. CASA, Working Paper nr. 9, University College London, UKGoogle Scholar
  19. Semboloni F (2000) The dynamic of an urban cellular automata model in a 3-d spatial pattern. In: XXI National Conference Aisre: Regional and Urban Growth in a Global Market, PalermoGoogle Scholar
  20. Semboloni F (2005) The CityDev project: an interactive multi-agents urban model on the web. In: Portugali J (ed) Complex Artificial Environments. Springer, Berlin, pp 155–164Google Scholar
  21. Semboloni F, Assfalg J, Armeni S, Gianassi R, Marsoni F (2004) CityDev, an interactive multi-agents model on the web. Computers environment and urban system 4: 45–64CrossRefGoogle Scholar
  22. Smith N (1987) Gentrification and the rent-gap. Annals of the Association of American Geographers 77: 462–465CrossRefGoogle Scholar
  23. Straatman B, White R, Engelen G (2004) Towards an automatic calibration procedure for constrained cellular automata. Computers, Environment and Urban Systems 28: 149–170CrossRefGoogle Scholar
  24. Taylor JL (1971) Instructional Planning System: a Gaming Simulation Approach to Urban Problems. The University Press, CambridgeGoogle Scholar
  25. Tesfatsion L (2002) Agent-based computational economics: Growing economies from the bottom up. Artificial Life 8: 55–82CrossRefGoogle Scholar
  26. Tobler WR (1970) A computer movie simulation urban growth in the Detroit region. Economic Geography 46: 234–240CrossRefGoogle Scholar
  27. Torrens PM, O’Sullivan D (2001) Cellular automata and urban simulation: where do we go from here? Environment and Planning B:Planning and Design 28:163–168CrossRefGoogle Scholar

Copyright information

© Physica-Verlag Heidelberg and Accademia di Architettura, Mendrisio, Switzerland 2008

Authors and Affiliations

  • Ferdinando Semboloni
    • 1
  1. 1.Center for the Study of Complex DynamicsUniversity of FlorenceItaly

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