ArticlePloS one2019
Sensitivity analysis of agent-based simulation utilizing massively parallel computation and interactive data visualization.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Agent-based modeling in cancer biomedicine: applications and tools for calibration and validation.Cancer biology & therapy · 2024Review
- Envisioning the Future of Personalized Medicine: Role and Realities of Digital Twins.Journal of medical Internet research · 2024Article
- The impact of climate change on the agriculture and the economy of Southern Gaul: New perspectives of agent-based modelling.PloS one · 2024Article
- Mobility constraints in segregation models.Scientific reports · 2023Article
- A description and sensitivity analysis of the ArchMatNet agent-based model.PeerJ. Computer science · 2023Article
- A vector-agent approach to (spatiotemporal) movement modelling and reasoning.Scientific reports · 2022Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An essential step in the analysis of agent-based simulation is sensitivity analysis, which namely examines the dependency of parameter values on simulation results. Although a number of approaches have been proposed for sensitivity analysis, they still have limitations in exhaustivity and interpretability. In this study, we propose a novel methodology for sensitivity analysis of agent-based simulation, MASSIVE (Massively parallel Agent-based Simulations and Subsequent Interactive Visualization-based Exploration). MASSIVE takes a unique paradigm, which is completely different from those of sensitivity analysis methods developed so far, By combining massively parallel computation and interactive data visualization, MASSIVE enables us to inspect a broad parameter space intuitively. We demonstrated the utility of MASSIVE by its application to cancer evolution simulation, which successfully identified conditions that generate heterogeneous tumors. We believe that our approach would be a de facto standard for sensitivity analysis of agent-based simulation in an era of evergrowing computational technology. All the results form our MASSIVE analysis are available at https://www.hgc.jp/~niiyan/massive.
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Registered trials
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