Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/230635 
Year of Publication: 
2015
Citation: 
[Journal:] Journal of Artificial Societies and Social Simulation [ISSN:] 1460-7425 [Volume:] 18 [Issue:] 4 [Publisher:] University of Surrey [Place:] Guildford [Year:] 2015
Publisher: 
University of Surrey, Guildford
Abstract: 
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 analyzing 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.
Subjects: 
agent-based modeling
methodologies
statistical test
sensitivity analysis
spatio-temporal heterogeneity
visualization
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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