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Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics

24 January 2019

Natalia Díaz Rodríguez

Papers citing "Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics"

39 / 39 papers shown

Title
Demystifying the Mechanisms Behind Emergent Exploration in Goal-conditioned RL Mahsa Bastankhah Grace Liu Dilip Arumugam Thomas L. Griffiths Benjamin Eysenbach 88 1 0 15 Oct 2025
Recurrent Auto-Encoders for Enhanced Deep Reinforcement Learning in Wilderness Search and Rescue Planning Jan-Hendrik Ewers David Anderson Douglas G. Thomson 143 0 0 26 Feb 2025
Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey Ruiqi Zhang Jing Hou Florian Walter Shangding Gu Jiayi Guan Florian Röhrbein Yali Du Panpan Cai G. Chen Alois Knoll 247 24 0 19 Aug 2024
BAKU: An Efficient Transformer for Multi-Task Policy Learning Siddhant Haldar Zhuoran Peng Lerrel Pinto OffRL 350 79 0 11 Jun 2024
CIER: A Novel Experience Replay Approach with Causal Inference in Deep Reinforcement Learning Jingwen Wang Dehui Du Yida Li Yiyang Li Yikang Chen AI4TS CML 110 0 0 14 May 2024
Algebras of actions in an agent's representations of the worldArtificial Intelligence (AIJ), 2023 Alexander Dean Eduardo Alonso Esther Mondragón 225 0 0 02 Oct 2023
Explainable Reinforcement Learning via a Causal World ModelInternational Joint Conference on Artificial Intelligence (IJCAI), 2023 Zhongwei Yu Jingqing Ruan Dengpeng Xing CML 331 24 0 04 May 2023
RT-1: Robotics Transformer for Real-World Control at Scale Anthony Brohan Noah Brown Justice Carbajal Yevgen Chebotar Joseph Dabis ... Ted Xiao Peng Xu Sichun Xu Tianhe Yu Brianna Zitkovich LM&Ro 439 1,675 0 13 Dec 2022
Neural Distillation as a State Representation Bottleneck in Reinforcement Learning Valentin Guillet D. Wilson Carlos Aguilar-Melchor Emmanuel Rachelson 135 1 0 05 Oct 2022
Kinova Gemini: Interactive Robot Grasping with Visual Reasoning and Conversational AIIEEE International Conference on Robotics and Biomimetics (ROBIO), 2022 Hanxiao Chen Jiankun Wang Max Meng 123 9 0 03 Sep 2022
Unsupervised Representation Learning in Deep Reinforcement Learning: A Review N. Botteghi M. Poel C. Brune SSL OffRL 317 22 0 27 Aug 2022
Explainable Reinforcement Learning on Financial Stock Trading using SHAP Satyam Kumar Mendhikar Vishal V. Ravi AIFin 127 9 0 18 Aug 2022
Achieving Goals using Reward Shaping and Curriculum LearningFuture Technologies Conference (FT), 2022 M. Anca Jonathan D. Thomas Dabal Pedamonti M. Studley Mark Hansen 151 2 0 06 Jun 2022
Learning Goal-Oriented Non-Prehensile Pushing in Cluttered ScenesIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2022 Nils Dengler D. Grossklaus Maren Bennewitz 201 24 0 04 Mar 2022
Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in IntralogisticsApplied Sciences (Appl. Sci.), 2022 Honghu Xue Benedikt Hein M. Bakr Georg Schildbach Bengt Abel Elmar Rueckert 213 21 0 23 Feb 2022
End-to-end Reinforcement Learning of Robotic Manipulation with Robust Keypoints RepresentationAsia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2022 Tianying Wang En Yen Puang Marcus Lee Yongpeng Wu Wei Jing SSL 175 5 0 12 Feb 2022
Scope and Sense of Explainability for AI-SystemsIntelligent Systems with Applications (ISA), 2021 Anastasia-Maria Leventi-Peetz T. Östreich Werner Lennartz Kai Weber 174 5 0 20 Dec 2021
Learning from learning machines: a new generation of AI technology to meet the needs of science L. Pion-Tonachini K. Bouchard Héctor García Martín S. Peisert W. B. Holtz ... Rick L. Stevens Mark Anderson Ken Kreutz-Delgado Michael W. Mahoney James B. Brown 207 9 0 27 Nov 2021
Acquisition of Chess Knowledge in AlphaZero Thomas McGrath A. Kapishnikov Nenad Tomašev Adam Pearce Demis Hassabis Been Kim Ulrich Paquet Vladimir Kramnik 389 188 0 17 Nov 2021
POAR: Efficient Policy Optimization via Online Abstract State Representation Learning Zhaorun Chen Siqi Fan Yuan Tan Liang Gong Binhao Chen Te Sun David Filliat Natalia Díaz Rodríguez Chengliang Liu OffRL 144 0 0 17 Sep 2021
Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces N. Botteghi K. Alaa M. Poel B. Sirmaçek C. Brune A. Mersha Stefano Stramigioli SSL 114 11 0 04 Jul 2021
Continual Learning in Deep Networks: an Analysis of the Last Layer Timothée Lesort Thomas George Irina Rish KELM 190 23 0 03 Jun 2021
VDSM: Unsupervised Video Disentanglement with State-Space Modeling and Deep Mixtures of ExpertsComputer Vision and Pattern Recognition (CVPR), 2021 M. Vowels Necati Cihan Camgöz Richard Bowden CoGe 272 8 0 12 Mar 2021
An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare Taylor W. Killian Haoran Zhang Jayakumar Subramanian Mehdi Fatemi Marzyeh Ghassemi OffRL 182 47 0 23 Nov 2020
Fast Reinforcement Learning with Incremental Gaussian Mixture ModelsIEEE International Joint Conference on Neural Network (IJCNN), 2020 R. Pinto 74 1 0 02 Nov 2020
Explainability in Deep Reinforcement Learning Alexandre Heuillet Fabien Couthouis Natalia Díaz Rodríguez XAI 773 313 0 15 Aug 2020
Visuomotor Mechanical Search: Learning to Retrieve Target Objects in Clutter Andrey Kurenkov Joseph C. Taglic Rohun Kulkarni Marcus Dominguez-Kuhne Animesh Garg Roberto Martín-Martín Silvio Savarese 170 49 0 13 Aug 2020
Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes Timothée Lesort CLL 269 23 0 01 Jul 2020
Extracting Latent State Representations with Linear Dynamics from Rich Observations Abraham Frandsen Rong Ge 110 1 0 29 Jun 2020
ShieldNN: A Provably Safe NN Filter for Unsafe NN Controllers James Ferlez Mahmoud M. Elnaggar Yasser Shoukry C. Fleming AAML 288 36 0 16 Jun 2020
DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics Stéphane Doncieux Nicolas Bredèche L. L. Goff Benoît Girard Alexandre Coninx ... Natalia Díaz Rodríguez David Filliat Timothy M. Hospedales A. E. Eiben Richard J. Duro 163 19 0 13 May 2020
Learning Group Structure and Disentangled Representations of Dynamical Environments Robin Quessard Thomas D. Barrett W. Clements DRL 149 22 0 17 Feb 2020
Deep Reinforcement Learning for Autonomous Driving: A Survey B. R. Kiran Ibrahim Sobh V. Talpaert Patrick Mannion A. A. Sallab S. Yogamani P. Pérez 616 2,058 0 02 Feb 2020
A survey on intrinsic motivation in reinforcement learning A. Aubret L. Matignon S. Hassas AI4CE 351 157 0 19 Aug 2019
DisCoRL: Continual Reinforcement Learning via Policy Distillation Kalifou René Traoré Hugo Caselles-Dupré Timothée Lesort Te Sun Guanghang Cai Natalia Díaz Rodríguez David Filliat OffRL 135 62 0 11 Jul 2019
Continual Learning for Robotics: Definition, Framework, Learning Strategies, Opportunities and ChallengesInformation Fusion (Inf. Fusion), 2019 Timothée Lesort Vincenzo Lomonaco Andrei Stoian Davide Maltoni David Filliat Natalia Díaz Rodríguez CLL 300 282 0 29 Jun 2019
Continual Reinforcement Learning deployed in Real-life using Policy Distillation and Sim2Real Transfer Kalifou René Traoré Hugo Caselles-Dupré Timothée Lesort Te Sun Natalia Díaz Rodríguez David Filliat CLL OffRL 201 47 0 11 Jun 2019
Symmetry-Based Disentangled Representation Learning requires Interaction with Environments Hugo Caselles-Dupré Michael Garcia Ortiz David Filliat DRL 188 69 0 30 Mar 2019
S-TRIGGER: Continual State Representation Learning via Self-Triggered Generative Replay Hugo Caselles-Dupré Michael Garcia Ortiz David Filliat 107 18 0 25 Feb 2019