ABSTRACT Agent-based models (ABM) are used to represent a variety of complex systems by simulating the local interactions between system components from which observable spatial patterns at the system-level emerge. Thus, the degree to which these interactions are represented correctly must be evaluated. Networks can be used to discretely represent and quantify interactions between system components and the emergent system structure. Therefore, the main objective of this study is to develop and implement a novel validation approach called the NEtworks for ABM Testing (NEAT) that integrates geographic information science, ABM approaches, and spatial network representations to simulate complex systems as measurable and dynamic spatial networks. The simulated spatial network structures are measured using graph theory and compared with empirical regularities of observed real networks. The approach is implemented to validate a theoretical ABM representing the spread of influenza in the City of Vancouver, Canada. Results demonstrate that the NEAT approach can validate whether the internal model processes are represented realistically, thus better enabling the use of ABMs in decision-making processes.

中文翻译：

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用于测试和验证基于地理空间网络代理的模型过程的 NEAT 方法：流感传播案例研究

摘要 基于代理的模型 (ABM) 用于通过模拟系统组件之间的局部交互来表示各种复杂系统，系统级可观察的空间模式从中出现。因此，必须评估正确表示这些交互的程度。网络可用于离散地表示和量化系统组件和紧急系统结构之间的交互。因此，本研究的主要目标是开发和实施一种称为 ABM 测试网络 (NEAT) 的新型验证方法，该方法集成了地理信息科学、ABM 方法和空间网络表示，以将复杂系统模拟为可测量的动态空间网络。使用图论测量模拟的空间网络结构，并与观察到的真实网络的经验规律进行比较。该方法用于验证代表加拿大温哥华市流感传播的理论 ABM。结果表明，NEAT 方法可以验证内部模型过程是否真实表示，从而更好地在决策过程中使用 ABM。