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.

翻译：Agent-based modeling（ABM）属于一种计算动态建模方法，可能对一些读者不太熟悉。 ABM通过将代理放置在环境中，并研究代理-代理和代理-环境交互的新兴结果，以了解复杂系统的行为。与隔间模型相比，ABM提供了更简单、更可伸缩、更灵活的异质性表示方法，能够捕捉动态和静态的网络和空间上下文，并能够考虑个体的历史情况。相反，隔间模型提供了更快的开发时间，需要更少的编程，计算要求较低，不随人口规模而扩展，并支持常规、延迟或随机微分方程的简明数学公式，从而推导出系统行为的一些属性。在本章中，介绍了基于Agent的模型的基本特征，讨论了Agent模型的优缺点，与隔间模型相比较，并回顾了两个基于Agent的传染病模型案例的实现。