activity
20182021
most citedIntervention Aided Reinforcement Learning for Safe and Practical Policy Optimization in Navigation

12 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2021★ 1 cited

Reinforcement Learning with Evolutionary Trajectory Generator: A General Approach for Quadrupedal Locomotion

Haojie Shi, Bo Zhou, Hongsheng Zeng +6

Recently reinforcement learning (RL) has emerged as a promising approach for quadrupedal locomotion, which can save the manual effort in conventional approaches such as designing s…

cs.LG2021★ 1 cited

ADER:Adapting between Exploration and Robustness for Actor-Critic Methods

Bo Zhou, Kejiao Li, Hongsheng Zeng +2

Combining off-policy reinforcement learning methods with function approximators such as neural networks has been found to lead to overestimation of the value function and sub-optim…

cs.AI2021★ 3 cited

Action Set Based Policy Optimization for Safe Power Grid Management

Bo Zhou, Hongsheng Zeng, Yuecheng Liu +3

Maintaining the stability of the modern power grid is becoming increasingly difficult due to fluctuating power consumption, unstable power supply coming from renewable energies, an…

cs.LG2019★ 6 cited

Efficient and Robust Reinforcement Learning with Uncertainty-based Value Expansion

Bo Zhou, Hongsheng Zeng, Fan Wang +2

By integrating dynamics models into model-free reinforcement learning (RL) methods, model-based value expansion (MVE) algorithms have shown a significant advantage in sample effici…

cs.RO2018★ 12 cited

Intervention Aided Reinforcement Learning for Safe and Practical Policy Optimization in Navigation

Fan Wang, Bo Zhou, Ke Chen +5

Combining deep neural networks with reinforcement learning has shown great potential in the next-generation intelligent control. However, there are challenges in terms of safety an…