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
Lessons in Cooperation: A Qualitative Analysis of Driver Sentiments towards Real-Time Advisory Systems from a Driving Simulator User Study
Aamir Hasan, Neeloy Chakraborty, Haonan Chen, Cathy Wu, Katherine Driggs-Campbell
On the Complexity of Learning to Cooperate with Populations of Socially Rational Agents
Robert Loftin, Saptarashmi Bandyopadhyay, Mustafa Mert Çelikok