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.

Designing and Developing an Agent-Based Model

Designing and Developing an Agent-Based Model

Chapter Outline

What are the questions that social scientists and geographers need to consider when designing and building an agent-based model? What design frameworks and software toolkits are available to use? What are their relative pros and cons? What methods are available for documenting design concepts and why are they useful to modellers? This chapter will introduce the core concepts and frameworks that can be used to plan, implement and disseminate geographical agent-based models.

3.1 Introduction

Although ABM [agent-based modelling] is technically simple, it is also conceptually deep. This unusual combination often leads to improper use. (Bonabeau, 2002)

What to leave out, what to include? It is neither possible, nor useful, to model everything. Therefore modellers always ...

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