Tools for Complexity Science

Abstract

In this chapter, we pose the question: what does the science of cities, and in particular, the mathematical modelling of cities, offer complexity science? A prior question, of course, is: what is complexity science? Complex systems are characterised by needing many variables to describe them and having strong interdependencies between the elements of the system. When represented mathematically, these interdependencies will typically be nonlinear relationships. Obvious examples of complex systems are human beings, brains, economies, ecosystems, languages and, of course, cities and regions. From the perspective of this book, the ‘systems, theory and methods’ framework is an important foundation. Everything we have asserted about cities and regions in this respect repeats itself for any complex system: the system of interest must be well defined, we must have a theory of how it works, and we must have a tool kit of methods to facilitate building models that represent the theory. This raises all the issues of scale and the interactions between different scales.