Observational Overfitting in Reinforcement Learning

6 December 2019

Stephen Tu

Papers citing "Observational Overfitting in Reinforcement Learning"

35 / 35 papers shown

Title
Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning Xinyue Wang Zhen Zhang OffRL CML 29 0 0 13 May 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
Task Aware Dreamer for Task Generalization in Reinforcement Learning Chengyang Ying Zhongkai Hao Xinning Zhou Hang Su Songming Liu Dong Yan Jun Zhu 69 3 0 17 Feb 2025
Evolution and The Knightian Blindspot of Machine Learning Joel Lehman Elliot Meyerson Tarek El-Gaaly Kenneth O. Stanley Tarin Ziyaee 86 1 0 22 Jan 2025
Disentangling Recognition and Decision Regrets in Image-Based Reinforcement Learning Alihan Hüyük A. R. Koblitz Atefeh Mohajeri M. Andrews OffRL 40 0 0 19 Sep 2024
Learning Causally Invariant Reward Functions from Diverse Demonstrations Ivan Ovinnikov Eugene Bykovets J. M. Buhmann CML 33 0 0 12 Sep 2024
Adversarial Style Transfer for Robust Policy Optimization in Deep Reinforcement Learning Md Masudur Rahman Yexiang Xue 29 4 0 29 Aug 2023
Efficient Deep Reinforcement Learning Requires Regulating Overfitting Qiyang Li Aviral Kumar Ilya Kostrikov Sergey Levine OffRL 24 31 0 20 Apr 2023
Dynamic Update-to-Data Ratio: Minimizing World Model Overfitting Nicolai Dorka Tim Welschehold Wolfram Burgard 16 3 0 17 Mar 2023
Expediting Distributed DNN Training with Device Topology-Aware Graph Deployment Shiwei Zhang Xiaodong Yi Lansong Diao Chuan Wu Siyu Wang W. Lin GNN 22 5 0 13 Feb 2023
CRC-RL: A Novel Visual Feature Representation Architecture for Unsupervised Reinforcement Learning Darshita Jain A. Majumder S. Dutta Swagat Kumar SSL 26 1 0 31 Jan 2023
Adversarial Cheap Talk Chris Xiaoxuan Lu Timon Willi Alistair Letcher Jakob N. Foerster AAML 24 17 0 20 Nov 2022
Scaling Laws for Reward Model Overoptimization Leo Gao John Schulman Jacob Hilton ALM 41 475 0 19 Oct 2022
Hyperbolic Deep Reinforcement Learning Edoardo Cetin B. Chamberlain Michael M. Bronstein Jonathan J. Hunt 43 20 0 04 Oct 2022
Look where you look! Saliency-guided Q-networks for generalization in visual Reinforcement Learning David Bertoin Adil Zouitine Mehdi Zouitine Emmanuel Rachelson 36 30 0 16 Sep 2022
Example When Local Optimal Policies Contain Unstable Control B. Song Jean-Jacques E. Slotine Quang-Cuong Pham 46 1 0 15 Sep 2022
The Alignment Problem from a Deep Learning Perspective Richard Ngo Lawrence Chan Sören Mindermann 59 183 0 30 Aug 2022
Bootstrap State Representation using Style Transfer for Better Generalization in Deep Reinforcement Learning Md Masudur Rahman Yexiang Xue OffRL 31 4 0 15 Jul 2022
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels Edoardo Cetin Philip J. Ball Steve Roberts Oya Celiktutan 30 36 0 03 Jul 2022
Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions Rui Yang Jie Wang Zijie Geng Mingxuan Ye Shuiwang Ji Bin Li Fengli Wu OOD 31 20 0 20 May 2022
The Primacy Bias in Deep Reinforcement Learning Evgenii Nikishin Max Schwarzer P. DÓro Pierre-Luc Bacon Aaron C. Courville OnRL 96 180 0 16 May 2022
Local Feature Swapping for Generalization in Reinforcement Learning David Bertoin Emmanuel Rachelson OOD 21 14 0 13 Apr 2022
Evolving Curricula with Regret-Based Environment Design Jack Parker-Holder Minqi Jiang Michael Dennis Mikayel Samvelyan Jakob N. Foerster Edward Grefenstette Tim Rocktaschel 31 117 0 02 Mar 2022
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems Jack Parker-Holder Raghunandan Rajan Xingyou Song André Biedenkapp Yingjie Miao ... Vu-Linh Nguyen Roberto Calandra Aleksandra Faust Frank Hutter Marius Lindauer AI4CE 33 100 0 11 Jan 2022
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability Dibya Ghosh Jad Rahme Aviral Kumar Amy Zhang Ryan P. Adams Sergey Levine OffRL 278 109 0 13 Jul 2021
Stabilizing Deep Q-Learning with ConvNets and Vision Transformers under Data Augmentation Nicklas Hansen H. Su Xiaolong Wang OffRL 26 134 0 01 Jul 2021
Generalization of Reinforcement Learning with Policy-Aware Adversarial Data Augmentation Hanping Zhang Yuhong Guo 22 23 0 29 Jun 2021
SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies Linxi Fan Guanzhi Wang De-An Huang Zhiding Yu Li Fei-Fei Yuke Zhu Anima Anandkumar OffRL 15 62 0 17 Jun 2021
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning Yiding Jiang Pierre Foret Scott Yak Daniel M. Roy H. Mobahi Gintare Karolina Dziugaite Samy Bengio Suriya Gunasekar Isabelle M Guyon Behnam Neyshabur Google Research OOD 24 55 0 14 Dec 2020
Automatic Data Augmentation for Generalization in Deep Reinforcement Learning Roberta Raileanu M. Goldstein Denis Yarats Ilya Kostrikov Rob Fergus OffRL 22 109 0 23 Jun 2020
Gradient Monitored Reinforcement Learning Mohammed Sharafath Abdul Hameed Gavneet Singh Chadha Andreas Schwung S. Ding 28 10 0 25 May 2020
Rotation, Translation, and Cropping for Zero-Shot Generalization Chang Ye Ahmed Khalifa Philip Bontrager Julian Togelius 32 38 0 27 Jan 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 338 11,684 0 09 Mar 2017
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 287 2,890 0 15 Sep 2016
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 119 577 0 27 Feb 2015