Autonomous Cooperation

Autonomous cooperation research focuses on enabling independent agents to collaboratively achieve complex tasks without centralized control. Current efforts utilize diverse approaches, including large language models (LLMs) for task allocation and planning, graph neural networks for optimizing communication in distributed systems like satellite constellations, and quantum-enhanced reinforcement learning for improved scalability and efficiency in autonomous mobility. This field is significant for advancing capabilities in areas such as large-scale robotics, space exploration, and industrial automation, driving progress in both algorithm design and the development of robust, scalable multi-agent systems.