Efficient Deep Reinforcement Learning Requires Regulating Overfitting

20 April 2023

Papers citing "Efficient Deep Reinforcement Learning Requires Regulating Overfitting"

30 / 30 papers shown

Title
Hyperspherical Normalization for Scalable Deep Reinforcement Learning Hojoon Lee Youngdo Lee Takuma Seno Donghu Kim Peter Stone Jaegul Choo 63 1 0 24 Feb 2025
Prioritized Generative Replay Renhao Wang Kevin Frans Pieter Abbeel Sergey Levine Alexei A. Efros OnRL DiffM 114 2 0 23 Oct 2024
MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL C. Voelcker Marcel Hussing Eric Eaton Amir-massoud Farahmand Igor Gilitschenski 41 1 0 11 Oct 2024
Bigger, Regularized, Optimistic: scaling for compute and sample-efficient continuous control Michal Nauman M. Ostaszewski Krzysztof Jankowski Piotr Milo's Marek Cygan OffRL 45 16 0 25 May 2024
The Curse of Diversity in Ensemble-Based Exploration Zhixuan Lin P. DÓro Evgenii Nikishin Rameswar Panda 42 1 0 07 May 2024
Learning Off-policy with Model-based Intrinsic Motivation For Active Online Exploration Yibo Wang Jiang Zhao OffRL OnRL 27 0 0 31 Mar 2024
Dissecting Deep RL with High Update Ratios: Combatting Value Divergence Marcel Hussing C. Voelcker Igor Gilitschenski Amir-massoud Farahmand Eric Eaton 39 3 0 09 Mar 2024
A Case for Validation Buffer in Pessimistic Actor-Critic Michal Nauman M. Ostaszewski Marek Cygan 34 0 0 01 Mar 2024
Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning Michal Nauman Michal Bortkiewicz Piotr Milo's Tomasz Trzciñski M. Ostaszewski Marek Cygan OffRL 30 17 0 01 Mar 2024
Efficient Sparse-Reward Goal-Conditioned Reinforcement Learning with a High Replay Ratio and Regularization Takuya Hiraoka OffRL 29 1 0 10 Dec 2023
Handling Cost and Constraints with Off-Policy Deep Reinforcement Learning Jared Markowitz Jesse Silverberg Gary Collins OffRL 23 0 0 30 Nov 2023
On the Theory of Risk-Aware Agents: Bridging Actor-Critic and Economics Michal Nauman Marek Cygan 35 1 0 30 Oct 2023
Grow Your Limits: Continuous Improvement with Real-World RL for Robotic Locomotion Laura M. Smith Yunhao Cao Sergey Levine OffRL 35 19 0 26 Oct 2023
Mind the Model, Not the Agent: The Primacy Bias in Model-based RL Zhongjian Qiao Jiafei Lyu Xiu Li 24 3 0 23 Oct 2023
One is More: Diverse Perspectives within a Single Network for Efficient DRL Yiqin Tan Ling Pan Longbo Huang OffRL 38 0 0 21 Oct 2023
Sim-to-Real Transfer of Adaptive Control Parameters for AUV Stabilization under Current Disturbance Thomas Chaffre J. Wheare A. Lammas Paulo E. Santos G. Chenadec Karl Sammut Benoit Clement 29 1 0 17 Oct 2023
AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents Jake Grigsby Linxi Fan Yuke Zhu OffRL LM&Ro 38 10 0 15 Oct 2023
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 16 0 11 Oct 2023
ACT: Empowering Decision Transformer with Dynamic Programming via Advantage Conditioning Chenxiao Gao Chenyang Wu Mingjun Cao Rui Kong Zongzhang Zhang Yang Yu OffRL 34 13 0 12 Sep 2023
PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning Hojoon Lee Hanseul Cho Hyunseung Kim Daehoon Gwak Joonkee Kim Jaegul Choo Se-Young Yun Chulhee Yun OffRL 82 26 0 19 Jun 2023
Off-Policy RL Algorithms Can be Sample-Efficient for Continuous Control via Sample Multiple Reuse Jiafei Lyu Le Wan Zongqing Lu Xiu Li OffRL 34 9 0 29 May 2023
Deep Reinforcement Learning with Plasticity Injection Evgenii Nikishin Junhyuk Oh Georg Ostrovski Clare Lyle Razvan Pascanu Will Dabney André Barreto OffRL 26 50 0 24 May 2023
Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning Mitsuhiko Nakamoto Yuexiang Zhai Anika Singh Max Sobol Mark Yi Ma Chelsea Finn Aviral Kumar Sergey Levine OffRL OnRL 114 108 0 09 Mar 2023
Prioritizing Samples in Reinforcement Learning with Reducible Loss Shivakanth Sujit Somjit Nath Pedro H. M. Braga Samira Ebrahimi Kahou 50 15 0 22 Aug 2022
The Primacy Bias in Deep Reinforcement Learning Evgenii Nikishin Max Schwarzer P. DÓro Pierre-Luc Bacon Rameswar Panda OnRL 96 180 0 16 May 2022
Is High Variance Unavoidable in RL? A Case Study in Continuous Control Johan Bjorck Carla P. Gomes Kilian Q. Weinberger 65 23 0 21 Oct 2021
A Workflow for Offline Model-Free Robotic Reinforcement Learning Aviral Kumar Anika Singh Stephen Tian Chelsea Finn Sergey Levine OffRL 143 85 0 22 Sep 2021
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine Aviral Kumar George Tucker Justin Fu OffRL GP 340 1,960 0 04 May 2020
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity Aditya Bhatt Daniel Palenicek Boris Belousov Max Argus Artemij Amiranashvili Thomas Brox Jan Peters 32 43 0 14 Feb 2019
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015