Agent-based models (ABMs) are an increasingly popular choice for simulating large systems of interacting components, and have been applied across a wide variety of natural and environmental systems. However, ABMs can be incredibly disparate and often opaque in their formulation, implementation, and analysis. This can impede critical assessment and re-implementation, and jeopardize the reproducibility and conclusions of ABM studies. In this review, we survey recent work towards standardization in ABM methodology in several aspects: model description and documentation, model implementation, and model analysis and inference.

Based on a critical review of the literature, focused on ABMs of environmental and natural systems, we describe a recurrent trade-off between flexibility and standardization in ABM methodology. We find that standard protocols for model documentation are beginning to establish, although their uptake by the ABM community is inhibited by their sometimes excessive level of detail. We highlight how implementation options now exist at all points along a spectrum from ad hoc, ‘from scratch’ implementations, to specific software offering ‘off-the-shelf’ ABM implementations. We outline how the main focal points of ABM analysis (behavioural and inferential analysis) are facing similar issues with similar approaches. While this active development of ABM analysis techniques brings additional methods to our analysis toolbox, it does not contribute to the development of a standardized framework, since the performance and design of these methods tends to be highly problem-specific. We therefore recommend that agent-based modellers should consider multiple approaches simultaneously when analysing their model. Well-documented software packages, and critical comparative reviews of such, will be important facilitators in these advances. ABMs can additionally make better use of developments in other fields working with high-dimensional problems, such as Bayesian statistics and machine learning.

基于代理的模型 (ABM) 是模拟大型交互组件系统的日益流行的选择，并已应用于各种自然和环境系统。然而，ABM 可能在其制定、实施和分析中非常不同，并且通常不透明。这可能会阻碍关键评估和重新实施，并危及 ABM 研究的可重复性和结论。在这篇评论中，我们从几个方面调查了最近在 ABM 方法标准化方面的工作：模型描述和文档、模型实现以及模型分析和推理。

基于对文献的批判性回顾，重点关注环境和自然系统的 ABM，我们描述了 ABM 方法的灵活性和标准化之间的反复权衡。我们发现模型文档的标准协议开始建立，尽管 ABM 社区对它们的采用受到有时过于详细的限制。我们强调了从临时的“从头开始”实施到提供“现成”ABM 实施的特定软件，实施选项现在如何存在于各个方面。我们概述了 ABM 分析的主要焦点（行为和推理分析）如何通过类似的方法面临类似的问题。虽然 ABM 分析技术的积极发展为我们的分析工具箱带来了更多的方法，它无助于标准化框架的开发，因为这些方法的性能和设计往往是高度特定于问题的。因此，我们建议基于代理的建模者在分析其模型时应同时考虑多种方法。有据可查的软件包，以及对此类软件包的批判性比较审查，将是这些进步的重要推动者。ABM 还可以更好地利用其他处理高维问题的领域的发展，例如贝叶斯统计和机器学习。以及对此类的批判性比较审查将成为这些进展的重要推动者。ABM 还可以更好地利用其他处理高维问题的领域的发展，例如贝叶斯统计和机器学习。以及对此类的批判性比较审查将成为这些进展的重要推动者。ABM 还可以更好地利用其他处理高维问题的领域的发展，例如贝叶斯统计和机器学习。