6 citations · 6 across the 2 of their papers we have counts for
2 papers
cs.LG2021
Efficiently Training On-Policy Actor-Critic Networks in Robotic Deep Reinforcement Learning with Demonstration-like Sampled Exploration
Zhaorun Chen, Binhao Chen, Shenghan Xie +4
In complex environments with high dimension, training a reinforcement learning (RL) model from scratch often suffers from lengthy and tedious collection of agent-environment intera…
cs.RO2020★ 6 cited
Exploration-efficient Deep Reinforcement Learning with Demonstration Guidance for Robot Control
Ke Lin, Liang Gong, Xudong Li +6
Although deep reinforcement learning (DRL) algorithms have made important achievements in many control tasks, they still suffer from the problems of sample inefficiency and unstabl…