A groundbreaking simulation models flies as agents operating in SE(3) space—combining 3D translations and rotations—with real-time reinforcement learning. Users manipulate attractors, repellents, and plumes to shape swarm behavior, revealing how generative proposals and GAN-like critics evolve collective movement. This fusion of differential geometry and AI offers new insights for robotics and autonomous systems.