39 citations · 60 across the 3 of their papers we have counts for
3 papers
cs.AI2019★ 10 cited
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…
cs.MA2019★ 11 cited
Learning Multi-agent Communication under Limited-bandwidth Restriction for Internet Packet Routing
Hangyu Mao, Zhibo Gong, Zhengchao Zhang +2
Communication is an important factor for the big multi-agent world to stay organized and productive. Recently, the AI community has applied the Deep Reinforcement Learning (DRL) to…
cs.AI2017★ 39 cited
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…