Learning Invariant Representations for Reinforcement Learning without Reconstruction

18 June 2020

Papers citing "Learning Invariant Representations for Reinforcement Learning without Reconstruction"

40 / 240 papers shown

Title
Zipfian environments for Reinforcement Learning Stephanie C. Y. Chan Andrew Kyle Lampinen Pierre Harvey Richemond Felix Hill OffRL 15 15 0 15 Mar 2022
The Unsurprising Effectiveness of Pre-Trained Vision Models for Control Simone Parisi Aravind Rajeswaran Senthil Purushwalkam Abhinav Gupta LM&Ro 34 187 0 07 Mar 2022
Weakly Supervised Disentangled Representation for Goal-conditioned Reinforcement Learning Zhifeng Qian Mingyu You Hongjun Zhou Bin He DRL OffRL 41 7 0 28 Feb 2022
Don't Touch What Matters: Task-Aware Lipschitz Data Augmentation for Visual Reinforcement Learning Zhecheng Yuan Guozheng Ma Yao Mu Bo Xia Bo Yuan Xueqian Wang Ping Luo Huazhe Xu 33 28 0 21 Feb 2022
Approximate Policy Iteration with Bisimulation Metrics Mete Kemertas Allan D. Jepson 37 7 0 06 Feb 2022
Efficient Embedding of Semantic Similarity in Control Policies via Entangled Bisimulation Martín Bertrán Walter A. Talbott Nitish Srivastava J. Susskind 45 3 0 28 Jan 2022
Mask-based Latent Reconstruction for Reinforcement Learning Tao Yu Zhizheng Zhang Cuiling Lan Yan Lu Zhibo Chen 24 44 0 28 Jan 2022
Transfer RL across Observation Feature Spaces via Model-Based Regularization Yanchao Sun Ruijie Zheng Xiyao Wang Andrew Cohen Furong Huang OOD OffRL 25 21 0 01 Jan 2022
Learning State Representations via Retracing in Reinforcement Learning Changmin Yu Dong Li Jianye Hao Jun Wang Neil Burgess 30 7 0 24 Nov 2021
Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning Dhruv Shah Peng Xu Yao Lu Ted Xiao Alexander Toshev Sergey Levine Brian Ichter OffRL 37 41 0 04 Nov 2021
TRAIL: Near-Optimal Imitation Learning with Suboptimal Data Mengjiao Yang Sergey Levine Ofir Nachum OffRL 41 42 0 27 Oct 2021
DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations Fei Deng Ingook Jang Sungjin Ahn VLM 29 62 0 27 Oct 2021
Learning Domain Invariant Representations in Goal-conditioned Block MDPs Beining Han Chongyi Zheng Harris Chan Keiran Paster Michael Ruogu Zhang Jimmy Ba OOD AI4CE 20 13 0 27 Oct 2021
Common Information based Approximate State Representations in Multi-Agent Reinforcement Learning Shitao Xiao V. Subramanian 29 9 0 25 Oct 2021
Block Contextual MDPs for Continual Learning Shagun Sodhani Franziska Meier Joelle Pineau Amy Zhang CLL 41 26 0 13 Oct 2021
Planning from Pixels in Environments with Combinatorially Hard Search Spaces Marco Bagatella Miroslav Olsák Michal Rolínek Georg Martius OffRL 21 6 0 12 Oct 2021
Action-Sufficient State Representation Learning for Control with Structural Constraints Erdun Gao Chaochao Lu Liu Leqi José Miguel Hernández-Lobato Clark Glymour Bernhard Schölkopf Kun Zhang 54 32 0 12 Oct 2021
Dropout Q-Functions for Doubly Efficient Reinforcement Learning Takuya Hiraoka Takahisa Imagawa Taisei Hashimoto Takashi Onishi Yoshimasa Tsuruoka 11 105 0 05 Oct 2021
Domain Generalization for Vision-based Driving Trajectory Generation Yunkai Wang Dongkun Zhang Yuxiang Cui Zexi Chen Wei Jing Junbo Chen R. Xiong Yue Wang 36 3 0 22 Sep 2021
Comparing Reconstruction- and Contrastive-based Models for Visual Task Planning Constantinos Chamzas M. Lippi Michael C. Welle Anastasia Varava Lydia E. Kavraki Danica Kragic SSL DRL OffRL 56 4 0 14 Sep 2021
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 281 109 0 13 Jul 2021
Evaluating the progress of Deep Reinforcement Learning in the real world: aligning domain-agnostic and domain-specific research J. Luis E. Crawley B. Cameron OffRL 25 6 0 07 Jul 2021
Stabilizing Deep Q-Learning with ConvNets and Vision Transformers under Data Augmentation Nicklas Hansen H. Su Xiaolong Wang OffRL 34 134 0 01 Jul 2021
Learning Task Informed Abstractions Xiang Fu Ge Yang Pulkit Agrawal Tommi Jaakkola 31 65 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 30 63 0 17 Jun 2021
Temporal Predictive Coding For Model-Based Planning In Latent Space Tung D. Nguyen Rui Shu Tu Pham Hung Bui Stefano Ermon OffRL 32 56 0 14 Jun 2021
Learning Markov State Abstractions for Deep Reinforcement Learning Cameron Allen Neev Parikh Omer Gottesman George Konidaris BDL OffRL 31 36 0 08 Jun 2021
PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning Tao Yu Cuiling Lan Wenjun Zeng Mingxiao Feng Zhizheng Zhang Zhibo Chen OffRL 20 46 0 08 Jun 2021
MICo: Improved representations via sampling-based state similarity for Markov decision processes Pablo Samuel Castro Tyler Kastner Prakash Panangaden Mark Rowland 48 35 0 03 Jun 2021
Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction Hongyao Tang Jianye Hao Guangyong Chen Pengfei Chen Cen Chen Yaodong Yang Lu Zhang Wulong Liu Zhaopeng Meng OffRL 35 4 0 03 Mar 2021
Offline Reinforcement Learning with Pseudometric Learning Robert Dadashi Shideh Rezaeifar Nino Vieillard Léonard Hussenot Olivier Pietquin M. Geist OffRL 39 40 0 02 Mar 2021
Model-Based Domain Generalization Alexander Robey George J. Pappas Hamed Hassani OOD 45 129 0 23 Feb 2021
HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving Sirui Xie Xiaojian Ma Peiyu Yu Yixin Zhu Ying Nian Wu Song-Chun Zhu 42 20 0 22 Feb 2021
Return-Based Contrastive Representation Learning for Reinforcement Learning Guoqing Liu Chuheng Zhang Li Zhao Tao Qin Jinhua Zhu Jian Li Nenghai Yu Tie-Yan Liu SSL OffRL 19 47 0 22 Feb 2021
Model-Invariant State Abstractions for Model-Based Reinforcement Learning Manan Tomar Amy Zhang Roberto Calandra Matthew E. Taylor Joelle Pineau 24 24 0 19 Feb 2021
Model-free Representation Learning and Exploration in Low-rank MDPs Aditya Modi Jinglin Chen A. Krishnamurthy Nan Jiang Alekh Agarwal OffRL 102 78 0 14 Feb 2021
The Distracting Control Suite -- A Challenging Benchmark for Reinforcement Learning from Pixels Austin Stone Oscar Ramirez K. Konolige Rico Jonschkowski 137 101 0 07 Jan 2021
DeepKoCo: Efficient latent planning with a task-relevant Koopman representation B. V. D. Heijden L. Ferranti Jens Kober Robert Babuška 16 6 0 25 Nov 2020
A Geometric Perspective on Self-Supervised Policy Adaptation Cristian Bodnar Karol Hausman Gabriel Dulac-Arnold Rico Jonschkowski SSL 44 5 0 14 Nov 2020
Agent Modelling under Partial Observability for Deep Reinforcement Learning Georgios Papoudakis Filippos Christianos Stefano V. Albrecht 24 61 0 16 Jun 2020