‘One Size Does Not Fit All’: A Roadmap of Purpose-Driven Mixed-Method Pathways for Sensitivity Analysis of Agent-Based Models

Ligmann-Zielinska, Arika; Siebers, Peer-Olaf; Magliocca, Nicholas; Parker, Dawn C.; Grimm, Volker; Du, Jing; Cenek, Martin; Radchuk, Viktoriia; Arbab, Nazia N.; Li, Sheng; Berger, Uta; Paudel, Rajiv; Robinson, Derek T.; Jankowski, Piotr; An, Li; Ye, Xinyue

doi:10.18564/jasss.4201

All Outputs (5)

On the quest for defining organisational plasticity: a community modelling experiment (2020)
Journal Article
Siebers, P., Herath, D. B., Bardone, E., Farahbakhsh, S., Knudsen, P. G., Madsen, J. K., …Secchi, D. (2021). On the quest for defining organisational plasticity: a community modelling experiment. Evidence-based HRM, 9(2), 126-138. https://doi.org/10.1108/ebhrm-09-2019-0079

Purpose - This viewpoint article is concerned with an attempt to advance Organisational Plasticity (OP) modelling concepts by using a novel community modelling framework (PhiloLab) from the Social Simulation community to drive the process of idea gen... Read More about On the quest for defining organisational plasticity: a community modelling experiment.

Specification testing of agent-based simulation using property-based testing (2020)
Journal Article
Thaler, J., & Siebers, P. (2020). Specification testing of agent-based simulation using property-based testing. Autonomous Agents and Multi-Agent Systems, 34(2), https://doi.org/10.1007/s10458-020-09473-8

The importance of Agent-Based Simulation (ABS) as scientific method to generate data for scientific models in general and for informed policy decisions in particular has been widely recognised. However, the important technique of code testing of impl... Read More about Specification testing of agent-based simulation using property-based testing.

Using unsupervised learning to partition 3D city scenes for distributed building energy microsimulation (2020)
Journal Article
Zakhary, S., Rosser, J., Siebers, P., Mao, Y., & Robinson, D. (2020). Using unsupervised learning to partition 3D city scenes for distributed building energy microsimulation. Environment and Planning B: Urban Analytics and City Science, 48(5), https://doi.org/10.1177/2399808320914313

An innovative approach to multi-method integrated assessment modelling of global climate change (2020)
Journal Article
Siebers, P. O., Lim, Z. E., Figueredo, G. P., & Hey, J. (2020). An innovative approach to multi-method integrated assessment modelling of global climate change. Journal of Artificial Societies and Social Simulation, 23(1), https://doi.org/10.18564/jasss.4209

© 2020, University of Surrey. All rights reserved. Modelling and simulation play an increasingly significant role in exploratory studies for informing policy makers on climate change mitigation strategies. There is considerable research being done in... Read More about An innovative approach to multi-method integrated assessment modelling of global climate change.

‘One Size Does Not Fit All’: A Roadmap of Purpose-Driven Mixed-Method Pathways for Sensitivity Analysis of Agent-Based Models (2020)
Journal Article
Ligmann-Zielinska, A., Siebers, P., Magliocca, N., Parker, D. C., Grimm, V., Du, J., …Ye, X. (2020). ‘One Size Does Not Fit All’: A Roadmap of Purpose-Driven Mixed-Method Pathways for Sensitivity Analysis of Agent-Based Models. Journal of Artificial Societies and Social Simulation, 23(1), Article 6. https://doi.org/10.18564/jasss.4201

Designing, implementing, and applying agent-based models (ABMs) requires a structured approach, part of which is a comprehensive analysis of the output to input variability in the form of uncertainty and sensitivity analysis (SA). The objective of th... Read More about ‘One Size Does Not Fit All’: A Roadmap of Purpose-Driven Mixed-Method Pathways for Sensitivity Analysis of Agent-Based Models.