activity
20172021
most citedACCNet: Actor-Coordinator-Critic Net for "Learning-to-Communicate" with Deep Multi-agent Reinforcement Learning

39 citations · 75 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL20219 cited

Speech-language Pre-training for End-to-end Spoken Language Understanding

Yao Qian, Ximo Bian, Yu Shi +4

End-to-end (E2E) spoken language understanding (SLU) can infer semantics directly from speech signal without cascading an automatic speech recognizer (ASR) with a natural language…

cs.AI2020

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…

cs.AI201910 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.AI20196 cited

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…

cs.MA201911 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.LG2018

Modelling the Dynamic Joint Policy of Teammates with Attention Multi-agent DDPG

Hangyu Mao, Zhengchao Zhang, Zhen Xiao +1

Modelling and exploiting teammates' policies in cooperative multi-agent systems have long been an interest and also a big challenge for the reinforcement learning (RL) community. T…