Publications
Massive multi-agent data-driven simulations of the github ecosystem
Abstract
Simulating and predicting planetary-scale techno-social systems poses heavy computational and modeling challenges. The DARPA SocialSim program set the challenge to model the evolution of GitHub, a large collaborative software-development ecosystem, using massive multi-agent simulations. We describe our best performing models and our agent-based simulation framework, which we are currently extending to allow simulating other planetary-scale techno-social systems. The challenge problem measured participant’s ability, given 30 months of meta-data on user activity on GitHub, to predict the next months’ activity as measured by a broad range of metrics applied to ground truth, using agent-based simulation. The challenge required scaling to a simulation of roughly 3 million agents producing a combined 30 million actions, acting on 6 million repositories with commodity hardware. It was also …
- Date
- September 22, 2025
- Authors
- Jim Blythe, John Bollenbacher, Di Huang, Pik-Mai Hui, Rachel Krohn, Diogo Pacheco, Goran Muric, Anna Sapienza, Alexey Tregubov, Yong-Yeol Ahn, Alessandro Flammini, Kristina Lerman, Filippo Menczer, Tim Weninger, Emilio Ferrara
- Conference
- Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection: 17th International Conference, PAAMS 2019, Ávila, Spain, June 26–28, 2019, Proceedings 17
- Pages
- 3-15
- Publisher
- Springer International Publishing