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Decision Making, Conflicts and Time in a Synergetic City

  • Juval PortugaliEmail author
Chapter
Part of the Understanding Complex Systems book series (UCS)

Abstract

This chapter extends and elaborates on ideas presented in the previous one. In particular we address the question how urban agents, e.g., persons or families, may take decisions about occupying specific locations in the city. This decision has to agree with an attractiveness function between agents and locations. While this appears a standard question of most if not all complexity-driven urban simulation models, the procedure outlined here is innovative by several means. First, in line with our claim in Part II that cities are dual complex systems, and in line with the notion of SIRN, the model presented in this chapter treats every individual agent in the city as a genuine self-organizing system. Capitalizing on the concepts of synergetics, the behavior of each agent is described by an order parameter that emerges as a result of interactions between the agent’s internally represented properties and aims, and the externally represented properties of locations in the city. Second, it explicitly implements the competition between agents as well as the (more abstract) competition between the available flats at the various locations in the city. The model shows how the competition between agents and flats simultaneously affects the attraction between them or, more colloquially speaking, the attractiveness of flats. Third, it explicitly considers changes in time in that the competition between agents over locations, as well as the attractiveness of locations to agents, is time-dependent. In more general terms, presented below is a dynamical model that searches for the optimal distributions of urban agents over locations. The model maximizes the global attractiveness of the ensemble and accounts for various conflicting situations. Its solutions show that, depending on initial conditions, both optimal as well as suboptimal configurations can be reached.

Keywords

Global Attractiveness Optimal Global State Macroscopic Pattern Attractive Location Urban Unit 
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.

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Dept. of Geography and the Human EnvironmentTel Aviv UniversityTel AvivIsrael

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