A Structural-Cognitive Approach to Urban Simulation Models

  • Juval Portugali


This paper focuses on two interrelated properties of the agent-base (AB) and cellular automata (CA) urban simulation models currently employed in the study cities: The global urban structures that emerge out of their dynamics plays no role in the dynamics itself and, agents’ behavior as postulated in these models disregards the basic principles of human cognition, behavior and action as revealed by cognitive science. These two properties are interrelated because empirical and theoretical studies in cognitive science indicate that agents’ behavior in cities is strongly influenced by the global structure of cities. The paper elaborates on the deep roots of these properties, identifies some of the major problems they entail, and suggests a structural-cognitive approach to urban simulation models.


Cellular Automaton Cognitive Science Cellular Automaton Global Structure Dissipative Structure 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Allen P (1981) The evolutionary paradigm of dissipative structures. In: Jantsch E (ed) The Evolutionary Vision. Westview Press, Boulder, pp 25–71Google Scholar
  2. Clancey WJ (1997) Situated cognition. Cambridge University Press, New YorkGoogle Scholar
  3. Christaller W (1966) Central Places in Southern Germany. Prentice-Hall, Englewook Cliffs, NJGoogle Scholar
  4. Franklin S (1997) Artificial Minds. MIT Press, Cambridge, MAGoogle Scholar
  5. Freeman WJ (1999) How Brains Make Up Their Minds. Weidenfeld & Nicolson, LondonGoogle Scholar
  6. Gardner H (1987) The Mind’s New Science. Basic Books, New YorkGoogle Scholar
  7. Golani I, Kafkafi N, Drai D (1999) Phenotyping stereotypic behaviour: collective variables, range of variation and predictability. Applied Animal Behaviour Science 65:191–220CrossRefGoogle Scholar
  8. Hagerstand T (1967) Innovation Diffusion as a Spatial Process. University of Chicago Press, ChicagoGoogle Scholar
  9. Haggett P, Cliff AD, Frey A (1977) Locational Models. Edward Arnold, LondonGoogle Scholar
  10. Haken H (1983) Synergetics: An Introduction. Springer, HeidelbergGoogle Scholar
  11. Haken H (1988, 2000) Information and Self-Organization: A Macroscopic Approach to Complex Systems. Springer, HeidelbergGoogle Scholar
  12. Haken H (1991, 2004) Synergetic Computers and Cognition. Springer, HeidelbergGoogle Scholar
  13. Haken H (1996) Principles of Brain Functioning. Springer, HeidelbergGoogle Scholar
  14. Haken H (2002) Complexity reduction. 10 Herbstakademie conference on Self-Organization, Kloster, Seeon.Google Scholar
  15. Haken H (1996) Principles of Brain Functioning. Springer, HeidelbergGoogle Scholar
  16. Haken H, Portugali J (1995) A synergetc approach to the self-organization of cities. Environment and Planning B: Planning and Design 22: 35–46CrossRefGoogle Scholar
  17. Haken H, Portugali J (1996) Synergetics, Inter-representation networks and cognitive maps. In Portugali J (ed.) The construction of cognitive maps. Kluwer academic publishers, Dordrecht, pp. 45–67CrossRefGoogle Scholar
  18. Johnson M (1987) The Body in the Mind: the bodily basis of meaning, imagination, and reason. The University of Chicago press, ChicagoGoogle Scholar
  19. Lakoff G (1987) Women, Fire and Dangerous Things: what can categories reveal about the mind. The University of Chicago press, ChicagoGoogle Scholar
  20. Losch A (1954) The Economics of Location. Yale University Press, New Haven, CNGoogle Scholar
  21. McLuhan M, Fiore Q (1967) The Medium is the Massage. Penguin books, LondonGoogle Scholar
  22. Mikhailov AS (1990) Foundation of Synergetics I. Springer, HeidelbergGoogle Scholar
  23. Nicolis G, Prigogine I (1977) Self-Organization in Nonequilibrium Systems: From Dissipative Structures to Order Through Fluctuations. Wiley, New YorkGoogle Scholar
  24. Portugali J (1999) Self-Organization and the City. Springer, HeidelbergGoogle Scholar
  25. Portugali J (2004) Toward a cognitive approach to urban dynamics. Environment and Planning B, Planning and Design 31: 589–613CrossRefGoogle Scholar
  26. Portugali J (2006) Complexity theory as a link between Space and Place. Environment and Planning A 38:4: 647–664CrossRefGoogle Scholar
  27. Portugali J (2002) The seven basic propositions of SIRN (Synergetic Inter-Representation Networks). Nonlinear Phenomena in Complex Systems 5:4: 428–444Google Scholar
  28. Portugali J (2005a) Cognitive maps are over 60. In: Mark D, Cohn A (eds) Spatial Information Theory, COSIT 2005. Springer Lectures in Computer Science series, BerlinGoogle Scholar
  29. Portugali J (2005b) The scope of complex artificial environments. In: Portugali J (ed) Complex Artificial Environments. Spriger, Complexity series, HeidelbergGoogle Scholar
  30. Portugali J (2005c) Complex artificial environments — the ESLab’s experience. In Portugali J (ed) Complex Artificial Environments. Spriger, Complexity series, HeidelbergGoogle Scholar
  31. Portugali J (1996) Inter-representation networks and cognitive maps. In: Portugali J (ed) The construction of cognitive maps. Kluwer academic publishers, Dordrecht, pp 11–43CrossRefGoogle Scholar
  32. Rumelhart DE, Smolensky P, McClelland JL, Hinton GE (1986) Schemata and sequential thought processes in PDP models. In: McClelland JL, Rumelhart DE Research Group (eds) Parallel Distributed Processing, Explorations in the Microstructure of Cognition. vol 2: Psychological and Biological Models. MIT Press, Cambridge, MA, pp 7–57Google Scholar
  33. Ryle G (1949) The Concept of Mind. Hutchinson’s University Library, LondonGoogle Scholar
  34. Simon HA (1981/1999) The Sciences of the Artificial. MIT Press, Cambridge, CAGoogle Scholar
  35. Tolman E (1948) Cognitive maps in rats and men. Psychological Review 56:144–155CrossRefGoogle Scholar
  36. Thunen JH von (1826, 1966) The Isolated State. Pergamon, OxfordGoogle Scholar
  37. Varela FJ, Thompson E, Rosch E (1994) The Embodied Mind. MIT Press, Cambridge MAGoogle Scholar
  38. Weidlich W (1987) Synergetics and social science. In: Graham R, Wunderlin A (eds) Lasers and Synergetics. Springer, Berlin, pp 238–256Google Scholar

Copyright information

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

Authors and Affiliations

  • Juval Portugali
    • 1
  1. 1.Environmental Simulation Laboratory (ESLab)Tel Aviv UniversityIsrael

Personalised recommendations