3 citations · 4 across the 6 of their papers we have counts for
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cs.LG2021★ 3 cited
VMAgent: Scheduling Simulator for Reinforcement Learning
Junjie Sheng, Shengliang Cai, Haochuan Cui +9
A novel simulator called VMAgent is introduced to help RL researchers better explore new methods, especially for virtual machine scheduling. VMAgent is inspired by practical virtua…
cs.LG2021★ 1 cited
Structured Diversification Emergence via Reinforced Organization Control and Hierarchical Consensus Learning
Wenhao Li, Xiangfeng Wang, Bo Jin +3
When solving a complex task, humans will spontaneously form teams and to complete different parts of the whole task, respectively. Meanwhile, the cooperation between teammates will…
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…