论文标题
用于动态和异质参数的基于代理的模型的自动校准框架
Automatic Calibration Framework of Agent-Based Models for Dynamic and Heterogeneous Parameters
论文作者
论文摘要
基于代理的模型（ABM）强调了模拟验证的重要性，例如定性面部验证和定量经验验证。特别是，我们通过调整ABM的模拟输入参数来重点介绍定量验证。这项研究引入了一个自动校准框架，该框架结合了建议的动态和异质校准方法。具体而言，动态校准通过自动捕获合适的仿真时间来调整仿真参数，将模拟结果拟合到现实世界数据。同时，异质校准通过调整与代理相关的参数群群群群降低了模拟和现实世界中个体之间的分布差异。
Agent-based models (ABMs) highlight the importance of simulation validation, such as qualitative face validation and quantitative empirical validation. In particular, we focused on quantitative validation by adjusting simulation input parameters of the ABM. This study introduces an automatic calibration framework that combines the suggested dynamic and heterogeneous calibration methods. Specifically, the dynamic calibration fits the simulation results to the real-world data by automatically capturing suitable simulation time to adjust the simulation parameters. Meanwhile, the heterogeneous calibration reduces the distributional discrepancy between individuals in the simulation and the real world by adjusting agent related parameters cluster-wisely.
