Near-Optimal Representation Learning for Hierarchical Reinforcement Learning

2 October 2018

Papers citing "Near-Optimal Representation Learning for Hierarchical Reinforcement Learning"

48 / 48 papers shown

Title
Dynamic Legged Ball Manipulation on Rugged Terrains with Hierarchical Reinforcement Learning Dongjie Zhu Zhuo Yang Tianhang Wu Luzhou Ge X. Li Qi Liu Zhaoxin Fan 29 0 0 21 Apr 2025
Behaviour Discovery and Attribution for Explainable Reinforcement Learning Rishav Rishav Somjit Nath Vincent Michalski Samira Ebrahimi Kahou FAtt OffRL 70 0 0 19 Mar 2025
CORD: Generalizable Cooperation via Role Diversity Kanefumi Matsuyama Kefan Su Jiangxing Wang Deheng Ye Zongqing Lu 40 0 0 04 Jan 2025
Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks Yoav Gelberg Tycho F. A. van der Ouderaa Mark van der Wilk Y. Gal AAML 40 4 0 10 Aug 2024
Coordinating Planning and Tracking in Layered Control Policies via Actor-Critic Learning Fengjun Yang Nikolai Matni OffRL 31 0 0 03 Aug 2024
Information-Theoretic State Variable Selection for Reinforcement Learning Charles Westphal Stephen Hailes Mirco Musolesi 26 3 0 21 Jan 2024
Adaptive trajectory-constrained exploration strategy for deep reinforcement learning Guojian Wang Faguo Wu Xiao Zhang Ning Guo Zhiming Zheng 33 3 0 27 Dec 2023
Universal Visual Decomposer: Long-Horizon Manipulation Made Easy Zichen Zhang Yunshuang Li Osbert Bastani Abhishek Gupta Dinesh Jayaraman Yecheng Jason Ma Luca Weihs 37 17 0 12 Oct 2023
Hieros: Hierarchical Imagination on Structured State Space Sequence World Models Paul Mattes Rainer Schlosser R. Herbrich 21 4 0 08 Oct 2023
Wasserstein Diversity-Enriched Regularizer for Hierarchical Reinforcement Learning Haorui Li Jiaqi Liang Linjing Li D. Zeng 11 0 0 02 Aug 2023
Learning Achievement Structure for Structured Exploration in Domains with Sparse Reward Zihan Zhou Animesh Garg OffRL 22 3 0 30 Apr 2023
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning Riashat Islam Hongyu Zang Anirudh Goyal Alex Lamb Kenji Kawaguchi Xin-hui Li Romain Laroche Yoshua Bengio Rémi Tachet des Combes OffRL AI4CE 23 9 0 01 Nov 2022
Flexible Attention-Based Multi-Policy Fusion for Efficient Deep Reinforcement Learning Zih-Yun Chiu Yi-Lin Tuan William Yang Wang Michael C. Yip OffRL 25 3 0 07 Oct 2022
An information-theoretic perspective on intrinsic motivation in reinforcement learning: a survey A. Aubret L. Matignon S. Hassas 34 35 0 19 Sep 2022
Contrastive Learning as Goal-Conditioned Reinforcement Learning Benjamin Eysenbach Tianjun Zhang Ruslan Salakhutdinov Sergey Levine SSL OffRL 28 139 0 15 Jun 2022
Discovering Intrinsic Reward with Contrastive Random Walk Zixuan Pan Zihao Wei Yidong Huang Aditya Gupta 17 0 0 23 Apr 2022
Learning Design and Construction with Varying-Sized Materials via Prioritized Memory Resets Yunfei Li Tao Kong Lei Li Yi Wu 43 4 0 12 Apr 2022
A Survey on Deep Reinforcement Learning-based Approaches for Adaptation and Generalization Pamul Yadav Ashutosh Mishra Junyong Lee Shiho Kim OffRL AI4CE 18 10 0 17 Feb 2022
SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisition Dylan Slack Yinlam Chow Bo Dai Nevan Wichers OffRL 24 7 0 10 Feb 2022
ASHA: Assistive Teleoperation via Human-in-the-Loop Reinforcement Learning S. Chen Jensen Gao S. Reddy Glen Berseth Anca Dragan Sergey Levine OffRL 36 11 0 05 Feb 2022
TRAIL: Near-Optimal Imitation Learning with Suboptimal Data Mengjiao Yang Sergey Levine Ofir Nachum OffRL 41 42 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
Hierarchical Skills for Efficient Exploration Jonas Gehring Gabriel Synnaeve Andreas Krause Nicolas Usunier 28 40 0 20 Oct 2021
Provable Hierarchy-Based Meta-Reinforcement Learning Kurtland Chua Qi Lei Jason D. Lee 22 5 0 18 Oct 2021
Context-Specific Representation Abstraction for Deep Option Learning Marwa Abdulhai Dong-Ki Kim Matthew D Riemer Miao Liu Gerald Tesauro Jonathan P. How OffRL 31 9 0 20 Sep 2021
Multi-Task Learning with Sequence-Conditioned Transporter Networks M. H. Lim Andy Zeng Brian Ichter Maryam Bandari Erwin Coumans Claire Tomlin S. Schaal Aleksandra Faust 37 14 0 15 Sep 2021
Robust Predictable Control Benjamin Eysenbach Ruslan Salakhutdinov Sergey Levine OffRL 24 44 0 07 Sep 2021
Unsupervised Skill Discovery with Bottleneck Option Learning Jaekyeom Kim Seohong Park Gunhee Kim 32 32 0 27 Jun 2021
Investigating the Role of Negatives in Contrastive Representation Learning Jordan T. Ash Surbhi Goel A. Krishnamurthy Dipendra Kumar Misra SSL 29 49 0 18 Jun 2021
Which Mutual-Information Representation Learning Objectives are Sufficient for Control? Kate Rakelly Abhishek Gupta Carlos Florensa Sergey Levine SSL 26 38 0 14 Jun 2021
Hierarchical Representation Learning for Markov Decision Processes Lorenzo Steccanella Simone Totaro Anders Jonsson 20 4 0 03 Jun 2021
From Motor Control to Team Play in Simulated Humanoid Football Siqi Liu Guy Lever Zhe Wang J. Merel S. M. Ali Eslami ... Tuomas Haarnoja Brendan D. Tracey K. Tuyls T. Graepel N. Heess 31 129 0 25 May 2021
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification Benjamin Eysenbach Sergey Levine Ruslan Salakhutdinov OffRL 34 50 0 23 Mar 2021
From Pixels to Legs: Hierarchical Learning of Quadruped Locomotion Deepali Jain Atil Iscen Ken Caluwaerts 23 35 0 23 Nov 2020
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning Anurag Ajay Aviral Kumar Pulkit Agrawal Sergey Levine Ofir Nachum OffRL OnRL 34 153 0 26 Oct 2020
Efficient Robotic Object Search via HIEM: Hierarchical Policy Learning with Intrinsic-Extrinsic Modeling Xin Ye Yezhou Yang 22 14 0 16 Oct 2020
RODE: Learning Roles to Decompose Multi-Agent Tasks Tonghan Wang Tarun Gupta Anuj Mahajan Bei Peng Shimon Whiteson Chongjie Zhang OffRL 30 203 0 04 Oct 2020
Data-efficient Hindsight Off-policy Option Learning Markus Wulfmeier Dushyant Rao Roland Hafner Thomas Lampe A. Abdolmaleki ... Michael Neunert Dhruva Tirumala Noah Y. Siegel N. Heess Martin Riedmiller OffRL 23 47 0 30 Jul 2020
Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning Tianren Zhang Shangqi Guo Tian Tan Xiaolin Hu Feng Chen 22 80 0 20 Jun 2020
Hierarchically Decoupled Imitation for Morphological Transfer D. Hejna Pieter Abbeel Lerrel Pinto LM&Ro 20 40 0 03 Mar 2020
Learning Functionally Decomposed Hierarchies for Continuous Control Tasks with Path Planning Sammy Christen Lukás Jendele Emre Aksan Otmar Hilliges OffRL 22 25 0 14 Feb 2020
Predictive Coding for Boosting Deep Reinforcement Learning with Sparse Rewards Xingyu Lu Stas Tiomkin Pieter Abbeel OffRL 27 4 0 21 Dec 2019
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning Dipendra Kumar Misra Mikael Henaff A. Krishnamurthy John Langford 21 151 0 13 Nov 2019
Learning Representations in Reinforcement Learning:An Information Bottleneck Approach Yingjun Pei Xinwen Hou SSL 29 10 0 12 Nov 2019
Dynamics-aware Embeddings William F. Whitney Rajat Agarwal Kyunghyun Cho Abhinav Gupta SSL 17 53 0 25 Aug 2019
Compositional Transfer in Hierarchical Reinforcement Learning Markus Wulfmeier A. Abdolmaleki Roland Hafner Jost Tobias Springenberg Michael Neunert Tim Hertweck Thomas Lampe Noah Y. Siegel N. Heess Martin Riedmiller 19 27 0 26 Jun 2019
Unsupervised State Representation Learning in Atari Ankesh Anand Evan Racah Sherjil Ozair Yoshua Bengio Marc-Alexandre Côté R. Devon Hjelm SSL 38 254 0 19 Jun 2019
Learning Compositional Neural Programs with Recursive Tree Search and Planning Thomas Pierrot Guillaume Ligner Scott E. Reed Olivier Sigaud Nicolas Perrin Alexandre Laterre David Kas Karim Beguir Nando de Freitas 36 41 0 30 May 2019