SocioVerse2: A Longitudinal Dynamic Social Simulation Framework under a Human-AI Co-evolutionary Paradigm
SocioVerse2 adds longitudinal interventions and researcher-controlled loops to generative-agent social simulation.
SocioVerse2 extends SocioVerse 1.0 into a human-AI co-evolutionary social simulation framework. A longitudinal loop evolves environments and forks counterfactual branches, while a controllable research loop treats the study as editable state. Infrastructure provides composable skills, researcher checkpoints, five persona pools, and an environment service over 21 point-in-time signal sources. Seven case studies cover canonical agent-based models, policy processes on real records, and macroeconomic nowcasting beyond the response model's knowledge cutoff.
- Two loops support longitudinal simulation and editable research state.
- Infrastructure uses five persona pools and 21 real-world signal sources.
- Validated on seven case studies, including macro nowcasting past the model cutoff.
- Code, data services, and a workbench are released open source.
- AI models
- SocioVerse2
From the original article
1 min read at arxiv.orgSocial simulation offers the social sciences an experimental instrument that the real world cannot supply, and generative agents have transformed it by acting as silicon samples that unite agent-based modeling with real behavioral data. Existing platforms verify collective behavior, align simulated populations with real societies in cross-sections, and employ autonomous agents for the research process.
By Xinnong Zhang · arxiv.org
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