34 citations · 40 across the 4 of their papers we have counts for
4 papers
Learning Communication Skills in Multi-task Multi-agent Deep Reinforcement Learning
Changxi Zhu, Mehdi Dastani, Shihan Wang
In multi-agent deep reinforcement learning (MADRL), agents can communicate with one another to perform a task in a coordinated manner. When multiple tasks are involved, agents can…
Reducing Variance Caused by Communication in Decentralized Multi-agent Deep Reinforcement Learning
Changxi Zhu, Mehdi Dastani, Shihan Wang
In decentralized multi-agent deep reinforcement learning (MADRL), communication can help agents to gain a better understanding of the environment to better coordinate their behavio…
A Survey of Multi-Agent Deep Reinforcement Learning with Communication
Changxi Zhu, Mehdi Dastani, Shihan Wang
Communication is an effective mechanism for coordinating the behaviors of multiple agents, broadening their views of the environment, and to support their collaborations. In the fi…
A Q-values Sharing Framework for Multiagent Reinforcement Learning under Budget Constraint
Changxi Zhu, Ho-fung Leung, Shuyue Hu +1
In teacher-student framework, a more experienced agent (teacher) helps accelerate the learning of another agent (student) by suggesting actions to take in certain states. In cooper…