文章基本信息

标题：The Complexities of Agent-Based Modeling Output Analysis
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作者：Ju-Sung Lee ; Tatiana Filatova ; Arika Ligmann-Zielinska 等
期刊名称：Journal of Artificial Societies and Social Simulation
印刷版ISSN：1460-7425
出版年度：2015
卷号：18
期号：4
页码：1-25
DOI：10.18564/jasss.2897
出版社：University of Surrey, Department of Sociology
摘要：The proliferation of agent-based models (ABMs) in recent decades has motivated model practitioners to improve the transparency, replicability, and trust in results derived from ABMs. The complexity of ABMs has risen in stride with advances in computing power and resources, resulting in larger models with complex interactions and learning and whose outputs are often high-dimensional and require sophisticated analytical approaches. Similarly, the increasing use of data and dynamics in ABMs has further enhanced the complexity of their outputs. In this article, we offer an overview of the state-of-the-art approaches in analysing and reporting ABM outputs highlighting challenges and outstanding issues. In particular, we examine issues surrounding variance stability (in connection with determination of appropriate number of runs and hypothesis testing), sensitivity analysis, spatio-temporal analysis, visualization, and effective communication of all these to non-technical audiences, such as various stakeholders.
关键词：Agent-Based Modelling; Methodologies; Statistical Test; Sensitivity Analysis; Spatio-Temporal Heterogeneity; Visualization