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Abstract
Computational modelling is increasingly gaining attention in archaeology and related disciplines. With the number of new models growing it is often difficult to evaluate their significance and the generality of the results. This is partially due to the narrow reporting of the model's results, which are often limited to those directly relevant to the research question posed in the first place. Although this is not an issue per se, models, if explored exhaustively, can provide a much wider perspective on the studied system. Sensitivity analysis is a widely recognised model exploration method for assessing the importance of different parameters on the model's behaviour. Such systematic exploration helps in unravelling the dynamics that drive the model and enable researchers to establish how robust the presented results are. Here we present a sensitivity analysis of MERCURY, a previously published archaeological agent-based model. The results show that two out of three of the original conclusions drawn on the basis of selective experiment design stand up to scrutiny. By describing in detail and providing a reusable script with detailed description of all steps of the sensitivity analysis we hope to promote this important model exploration technique among modellers and the wider archaeological audience.
Original language | English |
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Article number | 102974 |
Journal | Journal of Archaeological Science: Reports |
Volume | 38 |
ISSN | 2352-409X |
DOIs | |
Publication status | Published - Aug 2021 |
Keywords
- Agent-based modelling
- Ceramics
- Network science
- Roman archaeology
- Sensitivity analysis
- Simulation
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MINERVA: Understanding the centuries-long functioning of the Roman economy
Brughmans, T. (PI), Nørskov, V. (Collaborator), Sobotkova, A. (Collaborator), Wilson, A. (Collaborator), de Soto, P. (Collaborator), Franconi, T. (Collaborator), Sanchez-Genao, J. (Other), Borisova, E. (Collaborator), Pažout, A. (Participant), Coto Sarmiento, M. (Participant), Paulsen, L. B. (Collaborator), Møller, L. M. H. (Participant) & Dibbern, L. (Participant)
Sapere Aude - DFF Forskningsleder
01/01/2021 → 31/12/2024
Project: Research