62 citations · 170 across the 19 of their papers we have counts for
4 papers · 1 filter
Non-Linear Coordination Graphs
Yipeng Kang, Tonghan Wang, Xiaoran Wu +2
Value decomposition multi-agent reinforcement learning methods learn the global value function as a mixing of each agent's individual utility functions. Coordination graphs (CGs) r…
Birds of a Feather Flock Together: A Close Look at Cooperation Emergence via Multi-Agent RL
Heng Dong, Tonghan Wang, Jiayuan Liu +2
How cooperation emerges is a long-standing and interdisciplinary problem. Game-theoretical studies on social dilemmas reveal that altruistic incentives are critical to the emergenc…
ROMA: Multi-Agent Reinforcement Learning with Emergent Roles
Tonghan Wang, Heng Dong, Victor Lesser +1
The role concept provides a useful tool to design and understand complex multi-agent systems, which allows agents with a similar role to share similar behaviors. However, existing…
Convergence of Multi-Agent Learning with a Finite Step Size in General-Sum Games
Xinliang Song, Tonghan Wang, Chongjie Zhang
Learning in a multi-agent system is challenging because agents are simultaneously learning and the environment is not stationary, undermining convergence guarantees. To address thi…