Long Term Cooperation
Long-term cooperation, the sustained collaborative effort among agents towards shared goals, is a central research theme across diverse fields, aiming to understand its emergence and optimize its effectiveness. Current research focuses on developing algorithms and models, such as reinforcement learning, multi-agent systems, and large language models, to facilitate cooperation in various settings, including human-machine interaction, multi-robot systems, and distributed control. These advancements have significant implications for improving the efficiency and robustness of complex systems, from autonomous vehicle coordination to collaborative AI and human-centered design of assistive technologies.
Papers
Seamless Interaction Design with Coexistence and Cooperation Modes for Robust Human-Robot Collaboration
Zhe Huang, Ye-Ji Mun, Xiang Li, Yiqing Xie, Ninghan Zhong, Weihang Liang, Junyi Geng, Tan Chen, Katherine Driggs-Campbell
Mutual- and Self- Prototype Alignment for Semi-supervised Medical Image Segmentation
Zhenxi Zhang, Chunna Tian, Zhicheng Jiao