9 citations · 10 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 9 cited
Learning to Collaborate in Multi-Module Recommendation via Multi-Agent Reinforcement Learning without Communication
Xu He, Bo An, Yanghua Li +6
With the rise of online e-commerce platforms, more and more customers prefer to shop online. To sell more products, online platforms introduce various modules to recommend items wi…
cs.AI2019★ 1 cited
Inducing Cooperation via Team Regret Minimization based Multi-Agent Deep Reinforcement Learning
Runsheng Yu, Zhenyu Shi, Xinrun Wang +5
Existing value-factorized based Multi-Agent deep Reinforce-ment Learning (MARL) approaches are well-performing invarious multi-agent cooperative environment under thecen-tralized t…
cs.AI2019
Learning Efficient Multi-agent Communication: An Information Bottleneck Approach
Rundong Wang, Xu He, Runsheng Yu +3
We consider the problem of the limited-bandwidth communication for multi-agent reinforcement learning, where agents cooperate with the assistance of a communication protocol and a…