Off-Policy RL Algorithms Can be Sample-Efficient for Continuous Control via Sample Multiple Reuse

29 May 2023

Papers citing "Off-Policy RL Algorithms Can be Sample-Efficient for Continuous Control via Sample Multiple Reuse"

6 / 6 papers shown

Title
Novelty-based Sample Reuse for Continuous Robotics Control Ke Duan Kai Yang Houde Liu Xueqian Wang 24 0 0 17 Oct 2024
Cross-Domain Policy Adaptation by Capturing Representation Mismatch Jiafei Lyu Chenjia Bai Jingwen Yang Zongqing Lu Xiu Li 23 8 0 24 May 2024
Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages Guozheng Ma Lu Li Sen Zhang Zixuan Liu Zhen Wang Yixin Chen Li Shen Xueqian Wang Dacheng Tao OffRL 45 14 0 11 Oct 2023
The Primacy Bias in Deep Reinforcement Learning Evgenii Nikishin Max Schwarzer P. DÓro Pierre-Luc Bacon Aaron C. Courville OnRL 85 178 0 16 May 2022
Softmax Deep Double Deterministic Policy Gradients Ling Pan Qingpeng Cai Longbo Huang 72 86 0 19 Oct 2020
Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics Arsenii Kuznetsov Pavel Shvechikov Alexander Grishin Dmitry Vetrov 136 184 0 08 May 2020