Understanding the inner-workings of city-level agent-based models

基于主体的建模(ABM)正迅速成为社会科学家的标准工具。它能够代表个人、他们独特的特征和行为，为模拟人类行为提供了一个模板。通常，ABM被用来复制的应用系统，例如城市，充满了高度的复杂性和非线性动态。然而，我们缺乏工具来理解这些动态的相互作用以及它们在最终模型输出中所起的作用。如果我们要创建可以在政策领域使用的稳健模型，这一点尤为重要。这也是及时的；新形式的个人微数据(大数据)的增长只会增加ABM对个人如何使用和与系统交互的新见解。使用几个场景的输出，如健康或零售相关，从城市层面ABM，这个博士将评估和应用机器学习(ML)的一系列技术，以揭示ABM的内部工作原理。这将使您深入了解模型是哪些流程，以及哪些流程没有很好地复制。具体地说，目标是：1对ML的不同技术进行批判性评估--这为理解ABM规则的相互作用提供了最大的潜力？这将包括系统可视化的方法和统计评估2这些方法在ABM输出中的应用3 ML方法在ABM输出和批判性评估中的应用本博士学位的输出将是一个或多个受ML启发的方法的应用，这些方法将阐明ABM的黑箱性质。

Agent-based modelling (ABM) is rapidly becoming established as a standard tool for the socialscientist. Its ability to represent individuals, their unique characteristics and behaviour providea template for allowing simulations of human behaviour to be created. Typically, theapplication systems that ABMs are used to replicate, for example cities, are heavily imbuedwith complexity and non-linear dynamics. However, we lack the tools to understand theinterplay of these dynamics and the part they play in the final model output. This is particularlyimportant if we are to create robust models that can be used within the policy arena. This isalso timely; the growth in new forms of individual micro-data (big data) will only increase thepotential for ABM to give new insights into how individuals use and interact with systems.Using the outputs for several scenarios such as health or retail related, from a city levelABM, this PhD will evaluate and apply a range of techniques from Machine Learning (ML)for uncovering the inner-workings of ABM. This will give insight into which processes themodel is, and is not replicating well. Specifically, the aims will be:1 Critical evaluation of different techniques from ML - which offers the greatestpotential for understanding the interplay of ABM rules? This will include bothmethods for visualisation of the system as well as statistical appraisal.2 Adaption of these approaches for application to ABM outputs3 Application of ML approaches to ABM outputs and critical evaluation.The outputs of this PhD will be the application of one or more ML inspired approaches thatwill shed light on the black box nature of ABM.