3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 3 cited
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning
Shengyi Huang, Quentin Gallouédec, Florian Felten +30
In many Reinforcement Learning (RL) papers, learning curves are useful indicators to measure the effectiveness of RL algorithms. However, the complete raw data of the learning curv…
cs.LG2023
Adversarial Style Transfer for Robust Policy Optimization in Deep Reinforcement Learning
Md Masudur Rahman, Yexiang Xue
This paper proposes an algorithm that aims to improve generalization for reinforcement learning agents by removing overfitting to confounding features. Our approach consists of a m…
cs.LG2023
Accelerating Policy Gradient by Estimating Value Function from Prior Computation in Deep Reinforcement Learning
Md Masudur Rahman, Yexiang Xue
This paper investigates the use of prior computation to estimate the value function to improve sample efficiency in on-policy policy gradient methods in reinforcement learning. Our…