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Learning Invariant Representations for Reinforcement Learning without Reconstruction
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Learning Invariant Representations for Reinforcement Learning without Reconstruction

Amy Zhang
R. McAllister
Roberto Calandra
Y. Gal
Sergey Levine
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Papers citing "Learning Invariant Representations for Reinforcement Learning without Reconstruction"

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Title
Exploring Semantic Clustering in Deep Reinforcement Learning for Video Games
Exploring Semantic Clustering in Deep Reinforcement Learning for Video Games
Liang Zhang
Justin Lieffers
A. Pyarelal
140
0
0
25 Sep 2024
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn
Hongyao Tang
Glen Berseth
OffRL
139
5
0
07 Sep 2024
Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations
Yupei Yang
Erdun Gao
Fan Feng
Xinyue Wang
Shikui Tu
Lei Xu
CMLOODTTA
188
1
0
30 Jul 2024
Advanced deep-reinforcement-learning methods for flow control: group-invariant and positional-encoding networks improve learning speed and quality
Advanced deep-reinforcement-learning methods for flow control: group-invariant and positional-encoding networks improve learning speed and quality
Joogoo Jeon
Jean Rabault
Joel Vasanth
Francisco Alcántara-Ávila
Shilaj Baral
Ricardo Vinuesa
AI4CE
112
6
0
25 Jul 2024
On Causally Disentangled State Representation Learning for Reinforcement Learning based Recommender Systems
On Causally Disentangled State Representation Learning for Reinforcement Learning based Recommender Systems
Siyu Wang
Xiaocong Chen
Lina Yao
CML
75
0
0
18 Jul 2024
Collision Avoidance for Multiple UAVs in Unknown Scenarios with Causal Representation Disentanglement
Collision Avoidance for Multiple UAVs in Unknown Scenarios with Causal Representation Disentanglement
Jiafan Zhuang
Zihao Xia
Gaofei Han
Boxi Wang
Wenji Li
Dongliang Wang
Zhifeng Hao
Ruichu Cai
Zhun Fan
CML
123
0
0
04 Jul 2024
Disentangled Representations for Causal Cognition
Disentangled Representations for Causal Cognition
Filippo Torresan
Manuel Baltieri
CML
140
3
0
30 Jun 2024
DEAR: Disentangled Environment and Agent Representations for Reinforcement Learning without Reconstruction
DEAR: Disentangled Environment and Agent Representations for Reinforcement Learning without Reconstruction
Ameya Pore
Riccardo Muradore
Diego DallÁlba
DRL
125
4
0
30 Jun 2024
Diffusion Spectral Representation for Reinforcement Learning
Diffusion Spectral Representation for Reinforcement Learning
Dmitry Shribak
Chen-Xiao Gao
Yitong Li
Chenjun Xiao
Bo Dai
DiffM
150
7
0
23 Jun 2024
Learning Abstract World Model for Value-preserving Planning with Options
Learning Abstract World Model for Value-preserving Planning with Options
Rafael Rodríguez-Sánchez
George Konidaris
124
1
0
22 Jun 2024
Learning telic-controllable state representations
Learning telic-controllable state representations
Nadav Amir
Stas Tiomkin
149
0
0
20 Jun 2024
Leveraging Locality to Boost Sample Efficiency in Robotic Manipulation
Leveraging Locality to Boost Sample Efficiency in Robotic Manipulation
Tong Zhang
Yingdong Hu
Jiacheng You
Yang Gao
123
10
0
15 Jun 2024
SLR: Learning Quadruped Locomotion without Privileged Information
SLR: Learning Quadruped Locomotion without Privileged Information
Shiyi Chen
Zeyu Wan
Shiyang Yan
Chun Zhang
Weiyi Zhang
Qiang Li
Debing Zhang
F. Farrukh
82
7
0
07 Jun 2024
Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
Sergio Calo
Anders Jonsson
Gergely Neu
Ludovic Schwartz
Javier Segovia
OT
136
3
0
06 Jun 2024
iQRL -- Implicitly Quantized Representations for Sample-efficient Reinforcement Learning
iQRL -- Implicitly Quantized Representations for Sample-efficient Reinforcement Learning
Aidan Scannell
Kalle Kujanpää
Yi Zhao
Mohammadreza Nakhaei
Dieter Büchler
Joni Pajarinen
SSL
183
5
0
04 Jun 2024
Cross-Embodiment Robot Manipulation Skill Transfer using Latent Space Alignment
Cross-Embodiment Robot Manipulation Skill Transfer using Latent Space Alignment
Tianyu Wang
Dwait Bhatt
Xiaolong Wang
Nikolay Atanasov
158
9
0
04 Jun 2024
Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action Abstraction
Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action Abstraction
Yunhyeok Kwak
Inwoo Hwang
Dooyoung Kim
Sanghack Lee
Byoung-Tak Zhang
97
0
0
02 Jun 2024
Intrinsic Dynamics-Driven Generalizable Scene Representations for Vision-Oriented Decision-Making Applications
Intrinsic Dynamics-Driven Generalizable Scene Representations for Vision-Oriented Decision-Making Applications
Dayang Liang
Jinyang Lai
Yunlong Liu
128
0
0
30 May 2024
Causal Action Influence Aware Counterfactual Data Augmentation
Causal Action Influence Aware Counterfactual Data Augmentation
Núria Armengol Urpí
Marco Bagatella
Marin Vlastelica
Georg Martius
CML
90
7
0
29 May 2024
Cross-Domain Policy Adaptation by Capturing Representation Mismatch
Cross-Domain Policy Adaptation by Capturing Representation Mismatch
Jiafei Lyu
Chenjia Bai
Jingwen Yang
Zongqing Lu
Xiu Li
142
13
0
24 May 2024
State-Constrained Offline Reinforcement Learning
State-Constrained Offline Reinforcement Learning
Charles A. Hepburn
Yue Jin
Giovanni Montana
OffRL
139
0
0
23 May 2024
Meta-Control: Automatic Model-based Control Synthesis for Heterogeneous Robot Skills
Meta-Control: Automatic Model-based Control Synthesis for Heterogeneous Robot Skills
Tianhao Wei
Liqian Ma
Rui Chen
Weiye Zhao
Changliu Liu
155
7
0
18 May 2024
Learning Latent Dynamic Robust Representations for World Models
Learning Latent Dynamic Robust Representations for World Models
Ruixiang Sun
Hongyu Zang
Xin-hui Li
Riashat Islam
111
8
0
10 May 2024
Learning Planning Abstractions from Language
Learning Planning Abstractions from Language
Weiyu Liu
Geng Chen
Joy Hsu
Jiayuan Mao
Jiajun Wu
PINN
153
4
0
06 May 2024
Generalizing Multi-Step Inverse Models for Representation Learning to Finite-Memory POMDPs
Generalizing Multi-Step Inverse Models for Representation Learning to Finite-Memory POMDPs
Lili Wu
Ben Evans
Riashat Islam
Raihan Seraj
Yonathan Efroni
Alex Lamb
108
1
0
22 Apr 2024
Automated Discovery of Functional Actual Causes in Complex Environments
Automated Discovery of Functional Actual Causes in Complex Environments
Caleb Chuck
Sankaran Vaidyanathan
Stephen Giguere
Amy Zhang
David Jensen
S. Niekum
CML
152
2
0
16 Apr 2024
Hierarchical Decision Making Based on Structural Information Principles
Hierarchical Decision Making Based on Structural Information Principles
Xianghua Zeng
Hao Peng
Dingli Su
Angsheng Li
103
0
0
15 Apr 2024
SUGAR: Pre-training 3D Visual Representations for Robotics
SUGAR: Pre-training 3D Visual Representations for Robotics
Shizhe Chen
Ricardo Garcia Pinel
Ivan Laptev
Cordelia Schmid
149
21
0
01 Apr 2024
Learning Action-based Representations Using Invariance
Learning Action-based Representations Using Invariance
Max Rudolph
Caleb Chuck
Kevin Black
Misha Lvovsky
S. Niekum
Amy Zhang
110
1
0
25 Mar 2024
Towards Principled Representation Learning from Videos for Reinforcement Learning
Towards Principled Representation Learning from Videos for Reinforcement Learning
Dipendra Kumar Misra
Akanksha Saran
Tengyang Xie
Alex Lamb
John Langford
SSLOffRL
116
7
0
20 Mar 2024
Improving Out-of-Distribution Generalization of Learned Dynamics by Learning Pseudometrics and Constraint Manifolds
Improving Out-of-Distribution Generalization of Learned Dynamics by Learning Pseudometrics and Constraint Manifolds
Yating Lin
Glen Chou
Dmitry Berenson
OODD
125
0
0
18 Mar 2024
Multistep Inverse Is Not All You Need
Multistep Inverse Is Not All You Need
Alexander Levine
Peter Stone
Amy Zhang
AI4CE
126
4
0
18 Mar 2024
AD3: Implicit Action is the Key for World Models to Distinguish the Diverse Visual Distractors
AD3: Implicit Action is the Key for World Models to Distinguish the Diverse Visual Distractors
Yucen Wang
Shenghua Wan
Le Gan
Shuai Feng
De-Chuan Zhan
VGen
122
6
0
15 Mar 2024
DIGIC: Domain Generalizable Imitation Learning by Causal Discovery
DIGIC: Domain Generalizable Imitation Learning by Causal Discovery
Yang Chen
Yitao Liang
Zhouchen Lin
OODCML
92
0
0
29 Feb 2024
DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning
DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning
Jianxiong Li
Jinliang Zheng
Yinan Zheng
Liyuan Mao
Xiaoming Hu
...
Jihao Liu
Yu Liu
Jingjing Liu
Ya Zhang
Xianyuan Zhan
LM&RoOffRL
143
10
0
28 Feb 2024
Sample-Efficient Preference-based Reinforcement Learning with Dynamics Aware Rewards
Sample-Efficient Preference-based Reinforcement Learning with Dynamics Aware Rewards
Katherine Metcalf
Miguel Sarabia
Natalie Mackraz
B. Theobald
104
7
0
28 Feb 2024
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
Ruijie Zheng
Ching-An Cheng
Hal Daumé
Furong Huang
Andrey Kolobov
116
13
0
16 Feb 2024
Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss
Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss
Ruijie Zheng
Yongyuan Liang
Xiyao Wang
Shuang Ma
Hal Daumé
Huazhe Xu
John Langford
Praveen Palanisamy
Kalyan Shankar Basu
Furong Huang
198
8
0
09 Feb 2024
Do Transformer World Models Give Better Policy Gradients?
Do Transformer World Models Give Better Policy Gradients?
Michel Ma
Tianwei Ni
Clement Gehring
P. DÓro
Pierre-Luc Bacon
108
5
0
07 Feb 2024
The Essential Role of Causality in Foundation World Models for Embodied AI
The Essential Role of Causality in Foundation World Models for Embodied AI
Tarun Gupta
Wenbo Gong
Chao Ma
Nick Pawlowski
Agrin Hilmkil
...
Jianfeng Gao
Stefan Bauer
Danica Kragic
Bernhard Schölkopf
Cheng Zhang
120
21
0
06 Feb 2024
Understanding What Affects Generalization Gap in Visual Reinforcement Learning: Theory and Empirical Evidence
Understanding What Affects Generalization Gap in Visual Reinforcement Learning: Theory and Empirical Evidence
Jiafei Lyu
Le Wan
Xiu Li
Zongqing Lu
CMLOffRL
118
5
0
05 Feb 2024
Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning
Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning
Zizhao Wang
Caroline Wang
Xuesu Xiao
Yuke Zhu
Peter Stone
OffRL
69
6
0
23 Jan 2024
Closing the Gap between TD Learning and Supervised Learning -- A Generalisation Point of View
Closing the Gap between TD Learning and Supervised Learning -- A Generalisation Point of View
Raj Ghugare
Matthieu Geist
Glen Berseth
Benjamin Eysenbach
OffRL
161
22
0
20 Jan 2024
Bridging State and History Representations: Understanding Self-Predictive RL
Bridging State and History Representations: Understanding Self-Predictive RL
Tianwei Ni
Benjamin Eysenbach
Erfan Seyedsalehi
Michel Ma
Clement Gehring
Aditya Mahajan
Pierre-Luc Bacon
AI4TSAI4CE
157
34
0
17 Jan 2024
MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning
MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning
Bram Grooten
Tristan Tomilin
Gautham Vasan
Matthew E. Taylor
A. R. Mahmood
Meng Fang
Mykola Pechenizkiy
Decebal Constantin Mocanu
111
11
0
23 Dec 2023
ReRoGCRL: Representation-based Robustness in Goal-Conditioned Reinforcement Learning
ReRoGCRL: Representation-based Robustness in Goal-Conditioned Reinforcement Learning
Xiangyu Yin
Sihao Wu
Jiaxu Liu
Meng Fang
Xingyu Zhao
Xiaowei Huang
Wenjie Ruan
AAML
123
6
0
12 Dec 2023
The Generalization Gap in Offline Reinforcement Learning
The Generalization Gap in Offline Reinforcement Learning
Ishita Mediratta
Qingfei You
Minqi Jiang
Roberta Raileanu
OffRL
181
20
0
10 Dec 2023
On Task-Relevant Loss Functions in Meta-Reinforcement Learning and Online LQR
On Task-Relevant Loss Functions in Meta-Reinforcement Learning and Online LQR
Jaeuk Shin
Giho Kim
Howon Lee
Joonho Han
Insoon Yang
OffRL
113
1
0
09 Dec 2023
Provable Representation with Efficient Planning for Partial Observable Reinforcement Learning
Provable Representation with Efficient Planning for Partial Observable Reinforcement Learning
Hongming Zhang
Zhaolin Ren
Chenjun Xiao
Dale Schuurmans
Bo Dai
136
5
0
20 Nov 2023
Provably Efficient CVaR RL in Low-rank MDPs
Provably Efficient CVaR RL in Low-rank MDPs
Yulai Zhao
Wenhao Zhan
Xiaoyan Hu
Ho-fung Leung
Farzan Farnia
Wen Sun
Jason D. Lee
119
4
0
20 Nov 2023

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