Network Cities: A Complexity-Network Approach to Urban Dynamics and Development

Abstract

The aim of this proposed research is to develop an urban simulation model (USM) specifically designed to study the evolution and dynamics of systems of cities. It is innovative in three respects: First, in its structure – the proposed model is built as a superposition of two types of models; the first is an Agent Based Urban Simulation Model (ABUSM) that simulates the movement and interaction of agents in the urban space and the second is a network model that simulates the resultant urban network as it evolves. Secondly, it is innovative in the specific behavior of its agents – urban agents in our model act locally (as usual) but in order to do so, they perceive the city globally, i.e. they “think globally and act locally”. In our model, the local activities and interactions of agents give rise to the global urban structure and network that in turn affects the agents’ cognition, behavior, movement, and action in the city and so on in circular causality. The third aspect of innovation is connected with the specific urban phenomena it simulates – the vast majority of USM simulate the growth and expansion of urban systems but few simulate the reverse process of re-urbanization and gentrification; our model simultaneously captures the two processes and the interplay between them. Cities are complex systems by their nature. They have originally emerged, and are still developing, out of the interactions between many agents that are located and move in space and time. These interactions result in many links that create complex networks which form the city. In the last two decades CA and AB USM have provided the main approaches to studying the dynamics of cities as complex self-organizing systems. In the last few years, models based on the new science of networks have been introduced as well. This research direction is new in the conjunction it suggests between traditional network analysis (e.g. graph theory) and complexity theory. We introduce a new dynamic model for city development, based on the evolution and structure of urban networks.