  Agent-based modeling is a computational dynamic modeling technique that may
be less familiar to some readers. Agent-based modeling seeks to understand the
behaviour of complex systems by situating agents in an environment and studying
the emergent outcomes of agent-agent and agent-environment interactions. In
comparison with compartmental models, agent-based models offer simpler, more
scalable and flexible representation of heterogeneity, the ability to capture
dynamic and static network and spatial context, and the ability to consider
history of individuals within the model. In contrast, compartmental models
offer faster development time with less programming required, lower
computational requirements that do not scale with population, and the option
for concise mathematical formulation with ordinary, delay or stochastic
differential equations supporting derivation of properties of the system
behaviour. In this chapter, basic characteristics of agent-based models are
introduced, advantages and disadvantages of agent-based models, as compared
with compartmental models, are discussed, and two example agent-based
infectious disease models are reviewed.
