Synthetic population is of great importance when individual based simulation system try to investigate real case study where demographic attribute, localization and link between entities have an important impact on the dynamic of the model. In this context, to generate realistic agent population is a challenge: you must integrate a wide variety of data, most of which are not harmonized or standardized, to be able to create a realistic population with attributes that are key variables in your model. If we want social simulation to be able to represent complex social systems, we are in need of accessible, reusable and generic tools to endorse synthetic population generation. We propose a space to share ideas on principles and practices of synthetic population generation. We are pleased to invite you to submit your proposal to the Synthetic Population for Social Simulation (SP2S) special track to be held during Social Simulations Conference 2019.
Track chairs
- Kevin Chapuis, Post-doc, UMI 209 UMMISCO, Paris Sorbonne Université, IRD, Bondy, France
- Johan Barthelemy, Research Fellow, SMART Infrastructure Facility - Digital Living Lab,
University of Wollongong, NSW, Australia
List of presentations
| Authors | Title | Type of Submission | Presentation Time |
|---|---|---|---|
| Kevin Chapuis, Patrick Taillandier, Benoit Gaudou, Frederic Amblard and Samuel Thiriot | Gen*: an integrated tool for realistic agent population synthesis | Full paper | 30 min |
| Alperen Bektas and René Schumann | Using Mobility Profiles for Synthetic Population Generation | Full paper | 30 min |
| Aleksandra L. Mashkova, Olga A. Savina and Evgeniy Mashkov | Generating Synthetic Population for the Agent-Based Model of the Russian Federation Spatial Development | Extended abstract | 15 min |
| Kevin Chapuis and Patrick Taillandier | A brief review of synthetic population generation practices in agent-based social simulation | Extended abstract | 15 min |
| Morgane Dumont, Johan Barthelemy and Timoteo Carletti | Towards the evolution of synthetic population evolution in continuous time | Extended abstract | 15 min |