"Self-Organizing Agent Teams Learn to Reason Together" Most multi-agent systems are given a fixed way to collaborate. This paper shows agents can instead learn how to work together from experience, developing teamwork strategies that let them challenge, repair, and build on each other’s reasoning. With this setup, they were able to get 66.7% accuracy vs 48.8% for the strongest member and 59.0% for a perfect router. So the agents aren’t just selecting the best individual answer, but…