12 citations · 49 across the 33 of their papers we have counts for
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cs.LG2020★ 12 cited
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning
Wenhao Li, Bo Jin, Xiangfeng Wang +2
Traditional centralized multi-agent reinforcement learning (MARL) algorithms are sometimes unpractical in complicated applications, due to non-interactivity between agents, curse o…
cs.LG2020★ 7 cited
Learning Structured Communication for Multi-agent Reinforcement Learning
Junjie Sheng, Xiangfeng Wang, Bo Jin +5
This work explores the large-scale multi-agent communication mechanism under a multi-agent reinforcement learning (MARL) setting. We summarize the general categories of topology fo…
cs.LG2020
HMRL: Hyper-Meta Learning for Sparse Reward Reinforcement Learning Problem
Yun Hua, Xiangfeng Wang, Bo Jin +4
In spite of the success of existing meta reinforcement learning methods, they still have difficulty in learning a meta policy effectively for RL problems with sparse reward. In thi…