356 citations · 1k across the 31 of their papers we have counts for
4 papers · 1 filter
Better Exploration with Optimistic Actor-Critic
Kamil Ciosek, Quan Vuong, Robert Loftin +1
Actor-critic methods, a type of model-free Reinforcement Learning, have been successfully applied to challenging tasks in continuous control, often achieving state-of-the art perfo…
Striving for Simplicity and Performance in Off-Policy DRL: Output Normalization and Non-Uniform Sampling
Che Wang, Yanqiu Wu, Quan Vuong +1
We aim to develop off-policy DRL algorithms that not only exceed state-of-the-art performance but are also simple and minimalistic. For standard continuous control benchmarks, Soft…
Multi-task Batch Reinforcement Learning with Metric Learning
Jiachen Li, Quan Vuong, Shuang Liu +5
We tackle the Multi-task Batch Reinforcement Learning problem. Given multiple datasets collected from different tasks, we train a multi-task policy to perform well in unseen tasks…
How to pick the domain randomization parameters for sim-to-real transfer of reinforcement learning policies?
Quan Vuong, Sharad Vikram, Hao Su +2
Recently, reinforcement learning (RL) algorithms have demonstrated remarkable success in learning complicated behaviors from minimally processed input. However, most of this succes…