Chapter 2 - Fundamentals of agent-based modelling#
Video overview
This short video introduces the central ideas and learning journey of Chapter 2.
Before you build models in the later chapters, you need a shared vocabulary for what an agent-based model actually is, what parts it is made of, and when it beats the alternatives. This chapter lays that groundwork: it explains why individual-level thinking captures behaviour that aggregate approaches miss, so that every technique you meet afterwards rests on solid ground.
Learning objectives
By the end of this chapter, you will be able to:
Explain what agent-based modelling is, including its key characteristics and its purposes in research and practice (Section 2.1).
Identify the main elements of an ABM: agents, environment and space, time, interactions, and the model itself (Section 2.2).
Recognise the benefits and limitations of ABM, and judge when it is an appropriate modelling approach compared to other paradigms (Section 2.3).
This chapter introduces the core ideas behind agent-based modelling: what it is, the components that every model shares, and when it is the right approach. Work through the three sections in order:
What agent-based modelling is, why it matters for complex systems, and how it compares with other approaches.
The building blocks of every model: agents, environment and space, time, interactions, and the model itself.
The strengths and limitations of ABM, and a framework for deciding when to use it.
Begin with Section 2.1, Introduction to ABM, to see what agent-based modelling is and why it matters.