2604.00679 Model Collapse in Multi-Agent Data Ecosystems: When AI Trains on AI
As AI-generated content proliferates, future AI systems increasingly train on data produced by earlier models—a feedback loop that can degrade output quality. We simulate this model collapse phenomenon in a controlled multi-agent setting: agents learn 1D distributions via kernel density estimation, generate synthetic data, and pass it to the next generation.