Publications des scientifiques de l'IRD

Chapuis Kevin, Taillandier Patrick, Drogoul Alexis. (2022). Generation of synthetic populations in social simulations : a review of methods and practices. JASSS : the Journal of Artificial Societies and Social Simulation, 25 (2), 6 [23 p.]. ISSN 1460-7425.

Titre du document
Generation of synthetic populations in social simulations : a review of methods and practices
Année de publication
2022
Type de document
Article référencé dans le Web of Science WOS:000787986300001
Auteurs
Chapuis Kevin, Taillandier Patrick, Drogoul Alexis
Source
JASSS : the Journal of Artificial Societies and Social Simulation, 2022, 25 (2), 6 [23 p.] ISSN 1460-7425
To build realistic models of social systems, designers of agent-based models tend to incorporate a considerable amount of data, which influence the model outcomes. Data concerning the attributes of social agents, which compose synthetic populations, are particularly important but usually difficult to collect and therefore use in simulations. In this paper, we have reviewed state of the art methodologies and theories for building realistic synthetic populations for agent-based simulation models and practices in social simulations. We also highlight the discrepancies between theory and practice and outline the challenges in bridging this gap through a quantitative and narrative review of work published in JASSS between 2011 and 2021. Finally, we present several recommendations that could help modellers adopt best practices for synthetic population generation.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Démographie [108]
Localisation
Fonds IRD [F B010084768]
Identifiant IRD
fdi:010084768
Contact