Cooperative Agent

Cooperative agent research focuses on designing and analyzing systems where multiple agents work together to achieve a common goal, often in complex or uncertain environments. Current research emphasizes robust algorithms, such as those based on reinforcement learning (including multi-agent variants like Qmix and VDN), graph neural networks, and large language models (LLMs), to enable effective communication, coordination, and resilience to adversarial attacks or unreliable communication. These advancements are significant for various applications, including robotics, autonomous systems, and human-AI collaboration, by improving efficiency, robustness, and the ability to handle increasingly complex tasks. The field is also actively exploring methods for enhancing transparency and explainability in multi-agent systems.