This is the era of Big Data and computational social science. It is an era that requires tools which can do more than visualise data but also model the complex relation between data and human action, and interaction. Agent-Based Models (ABM) - computational models which simulate human action and interaction – do just that. This textbook explains how to design and build ABM and how to link the models to Geographical Information Systems. It guides you from the basics through to constructing more complex models which work with data and human behaviour in a spatial context. All of the fundamental concepts are explained and related to practical examples to facilitate learning (with models developed in NetLogo with all code examples available on the accompanying website). You will be able to use these models to develop your own applications and link, where appropriate, to Geographical Information Systems. All of the key ideas and methods are explained in detail: • geographical modelling; • an introduction to ABM; • the fundamentals of Geographical Information Science; • why ABM and GIS; • using QGIS; • designing and building an ABM; • calibration and validation; • modelling human behaviour; • visualisation and 3D ABM; • using Big Geosocial Data, GIS and ABM. An applied primer, that provides fundamental knowledge and practical skills, it will provide you with the skills to build and run your own models, and to begin your own research projects.
Chapter 11: Alternative Modelling Approaches
Alternative Modelling Approaches
Agent-based modelling is one of the most popular approaches used in social and spatial simulation. However, there are several other alternative approaches that are commonly used, including cellular automata, microsimulation, discreet event simulation, system dynamics and spatial interaction models. This chapter presents an overview of these other approaches, giving simple examples of how they can be used and summarising the main differences between them. To compare them, the chapter will consider the same scenario throughout: that of the spread of a disease modelled using a susceptible–infected–recovered epidemic model. This shows that while the same general patterns emerge, the mechanics can be very different. The chapter ends with a discussion and summary.
While this book is primarily concerned with ...