PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning

19 June 2023

Daehoon Gwak

Papers citing "PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning"

31 / 31 papers shown

Title
Plasticine: Accelerating Research in Plasticity-Motivated Deep Reinforcement Learning Mingqi Yuan Qi Wang Guozheng Ma Bo-wen Li Xin Jin Yunbo Wang Xiaokang Yang Wenjun Zeng D. Tao OffRL AI4CE 30 0 0 24 Apr 2025
A Champion-level Vision-based Reinforcement Learning Agent for Competitive Racing in Gran Turismo 7 Hojoon Lee Takuma Seno Jun Jet Tai K. Subramanian Kenta Kawamoto Peter Stone Peter R. Wurman 17 0 0 12 Apr 2025
Understanding Flatness in Generative Models: Its Role and Benefits Taehwan Lee Kyeongkook Seo Jaejun Yoo Sung Whan Yoon DiffM 51 0 0 14 Mar 2025
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
Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss Sangyeon Park Isaac Han Seungwon Oh Kyung-Joong Kim 54 2 0 03 Feb 2025
Reward Fine-Tuning Two-Step Diffusion Models via Learning Differentiable Latent-Space Surrogate Reward Zhiwei Jia Yuesong Nan Huixi Zhao Gengdai Liu EGVM 80 0 0 22 Nov 2024
DASH: Warm-Starting Neural Network Training in Stationary Settings without Loss of Plasticity Baekrok Shin Junsoo Oh Hanseul Cho Chulhee Yun AI4CE 33 1 0 30 Oct 2024
SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning Hojoon Lee Dongyoon Hwang Donghu Kim Hyunseung Kim Jun Jet Tai K. Subramanian Peter R. Wurman Jaegul Choo Peter Stone Takuma Seno OffRL 49 6 0 13 Oct 2024
MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL C. Voelcker Marcel Hussing Eric Eaton Amir-massoud Farahmand Igor Gilitschenski 36 1 0 11 Oct 2024
Neuroplastic Expansion in Deep Reinforcement Learning Jiashun Liu J. Obando-Ceron Aaron C. Courville L. Pan 31 3 0 10 Oct 2024
Can Learned Optimization Make Reinforcement Learning Less Difficult? Alexander David Goldie Chris Xiaoxuan Lu Matthew Jackson Shimon Whiteson Jakob N. Foerster 32 3 0 09 Jul 2024
Normalization and effective learning rates in reinforcement learning Clare Lyle Zeyu Zheng Khimya Khetarpal James Martens H. V. Hasselt Razvan Pascanu Will Dabney 14 7 0 01 Jul 2024
Investigating Pre-Training Objectives for Generalization in Vision-Based Reinforcement Learning Donghu Kim Hojoon Lee Kyungmin Lee Dongyoon Hwang Jaegul Choo OffRL 14 1 0 10 Jun 2024
A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning Arthur Juliani Jordan T. Ash OffRL OnRL CLL 28 0 0 29 May 2024
Diverse Feature Learning by Self-distillation and Reset Sejik Park CLL 24 1 0 29 Mar 2024
Reset & Distill: A Recipe for Overcoming Negative Transfer in Continual Reinforcement Learning Hongjoon Ahn Jinu Hyeon Youngmin Oh Bosun Hwang Taesup Moon CLL OnRL 16 2 0 08 Mar 2024
A Case for Validation Buffer in Pessimistic Actor-Critic Michal Nauman M. Ostaszewski Marek Cygan 27 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 17 16 0 01 Mar 2024
Disentangling the Causes of Plasticity Loss in Neural Networks Clare Lyle Zeyu Zheng Khimya Khetarpal H. V. Hasselt Razvan Pascanu James Martens Will Dabney AI4CE 45 30 0 29 Feb 2024
In value-based deep reinforcement learning, a pruned network is a good network J. Obando-Ceron Aaron C. Courville Pablo Samuel Castro OffRL 25 18 0 19 Feb 2024
DistiLLM: Towards Streamlined Distillation for Large Language Models Jongwoo Ko Sungnyun Kim Tianyi Chen SeYoung Yun 41 25 0 06 Feb 2024
Efficient Sparse-Reward Goal-Conditioned Reinforcement Learning with a High Replay Ratio and Regularization Takuya Hiraoka OffRL 12 1 0 10 Dec 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 35 14 0 11 Oct 2023
Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima Dongkuk Si Chulhee Yun 26 15 0 16 Jun 2023
Train Flat, Then Compress: Sharpness-Aware Minimization Learns More Compressible Models Clara Na Sanket Vaibhav Mehta Emma Strubell 51 19 0 25 May 2022
The Primacy Bias in Deep Reinforcement Learning Evgenii Nikishin Max Schwarzer P. DÓro Pierre-Luc Bacon Aaron C. Courville OnRL 83 178 0 16 May 2022
Sharpness-Aware Minimization Improves Language Model Generalization Dara Bahri H. Mobahi Yi Tay 113 82 0 16 Oct 2021
Improving Generalization in Reinforcement Learning with Mixture Regularization Kaixin Wang Bingyi Kang Jie Shao Jiashi Feng 104 113 0 21 Oct 2020
Decoupling Representation Learning from Reinforcement Learning Adam Stooke Kimin Lee Pieter Abbeel Michael Laskin SSL DRL 255 337 0 14 Sep 2020
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine Aviral Kumar George Tucker Justin Fu OffRL GP 321 1,662 0 04 May 2020
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 273 2,696 0 15 Sep 2016