A modular modelling framework for hypotheses testing in the simulation of urbanisation

TL;DR

This paper introduces a modular agent-based modelling framework to test hypotheses about urbanisation processes over large territories and long periods, using evolutionary algorithms for calibration and comparison.

Contribution

It develops a flexible, modular modelling approach for simulating urban evolution, allowing systematic testing and comparison of competing hypotheses in a virtual laboratory.

Findings

The framework effectively simulates urbanisation patterns in the former Soviet Union.

It identifies the best model structures based on evaluation criteria.

The approach addresses equifinality by comparing multiple mechanisms.

Abstract

In this paper, we present a modelling experiment developed to study systems of cities and processes of urbanisation in large territories over long time spans. Building on geographical theories of urban evolution, we rely on agent-based models to 1/ formalise complementary and alternative hypotheses of urbanisation and 2/ explore their ability to simulate observed patterns in a virtual laboratory. The paper is therefore divided into two sections : an overview of the mechanisms implemented to represent competing hypotheses used to simulate urban evolution; and an evaluation of the resulting model structures in their ability to simulate - efficiently and parsimoniously - a system of cities (the Former Soviet Union) over several periods of time (before and after the crash of the USSR). We do so using a modular framework of model-building and evolutionary algorithms for the calibration of several model structures. This project aims at tackling equifinality in systems dynamics by confronting different mechanisms with similar evaluation criteria. It enables the identification of the best-performing models with respect to the chosen criteria by scanning automatically the parameter along with the space of model structures (as combinations of modelled dynamics).