External Control

External control research focuses on developing methods to precisely manipulate and regulate the behavior of complex systems, ranging from robots and large language models to physical processes and biological systems. Current research emphasizes the development of robust and efficient control algorithms, often leveraging deep reinforcement learning, model predictive control, and generative models, alongside novel architectures like hybrid systems and multi-agent approaches. These advancements are crucial for improving the performance, safety, and adaptability of autonomous systems across diverse applications, from robotics and manufacturing to healthcare and environmental monitoring. The development of more efficient and generalizable control methods remains a key focus.