39 citations · 75 across the 5 of their papers we have counts for
4 papers · 1 filter
Reward Design in Cooperative Multi-agent Reinforcement Learning for Packet Routing
Hangyu Mao, Zhibo Gong, Zhen Xiao
In cooperative multi-agent reinforcement learning (MARL), how to design a suitable reward signal to accelerate learning and stabilize convergence is a critical problem. The global…
Learning Agent Communication under Limited Bandwidth by Message Pruning
Hangyu Mao, Zhengchao Zhang, Zhen Xiao +2
Communication is a crucial factor for the big multi-agent world to stay organized and productive. Recently, Deep Reinforcement Learning (DRL) has been applied to learn the communic…
Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning
Hangyu Mao, Wulong Liu, Jianye Hao +5
Social psychology and real experiences show that cognitive consistency plays an important role to keep human society in order: if people have a more consistent cognition about thei…
ACCNet: Actor-Coordinator-Critic Net for "Learning-to-Communicate" with Deep Multi-agent Reinforcement Learning
Hangyu Mao, Zhibo Gong, Yan Ni +1
Communication is a critical factor for the big multi-agent world to stay organized and productive. Typically, most previous multi-agent "learning-to-communicate" studies try to pre…