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Urban Growth Processes Joining Cellular Automata and Multiagent Systems. Part 1: Theory and Models

Author

Listed:
  • Alberto Vancheri
  • Paolo Giordano
  • Denise Andrey
  • Sergio Albeverio

    (Universität Bonn, Institut für Angewandte Mathematik, Abt. Stochastik, Wegelerstrasse 6, D-53115 Bonn, Germany)

Abstract

A new modelling framework for the study of the dynamics of urban systems is proposed. We generalize the notion of cellular automaton, using continuous variables to describe the state of a cell. The time evolution is given by Poisson-distributed stochastic jumps corresponding to urban interactions, with intensities depending on the configuration of the system in a suitable set of neighbourhoods. These interactions result from decision processes of populations of cognitive agents modelled in the framework of fuzzy decision theory. The behaviour of agents is driven by goals and constraints, partially defined using a fuzzy logic formalization of a real estate appraisal method based on the evaluation of the attractiveness of a terrain for different land uses. Randomness of the dynamics is a consequence of the fuzziness of these decisions. Hence the model can be seen as a multiagent system with sound mathematical foundation. For example, the use of a continuum-valued state space enables us to prove that the expectation of state variables verify a system of differential equations, and thus to study the system from a dynamical systems theory perspective. In this paper we present the theoretical setting, leaving the applications to a second paper.

Suggested Citation

  • Alberto Vancheri & Paolo Giordano & Denise Andrey & Sergio Albeverio, 2008. "Urban Growth Processes Joining Cellular Automata and Multiagent Systems. Part 1: Theory and Models," Environment and Planning B, , vol. 35(4), pages 723-739, August.
    • Handle: RePEc:sae:envirb:v:35:y:2008:i:4:p:723-739
    DOI: 10.1068/b31080a
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    References listed on IDEAS

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    1. Claes Andersson & Steen Rasmussen & Roger White, 2002. "Urban Settlement Transitions," Environment and Planning B, , vol. 29(6), pages 841-865, December.
    2. Hołyst, Janusz A. & Kacperski, Krzysztof & Schweitzer, Frank, 2000. "Phase transitions in social impact models of opinion formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 285(1), pages 199-210.
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    Cited by:

    1. Jiangfeng She & Zhongqing Guan & Fangfang Cai & Lijie Pu & Junzhong Tan & Tao Chen, 2017. "Simulation of Land Use Changes in a Coastal Reclaimed Area with Dynamic Shorelines," Sustainability, MDPI, vol. 9(3), pages 1-19, March.

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