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A Unified View on Solving Objective Mismatch in Model-Based Reinforcement Learning

10 October 2023

Papers citing "A Unified View on Solving Objective Mismatch in Model-Based Reinforcement Learning"

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Title
MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL C. Voelcker Marcel Hussing Eric Eaton Amir-massoud Farahmand Igor Gilitschenski 93 4 0 11 Oct 2024
Understanding Self-Predictive Learning for Reinforcement Learning Yunhao Tang Z. Guo Pierre Harvey Richemond Bernardo Avila-Pires Yash Chandak ... S. Thakoor Will Dabney Bilal Piot Daniele Calandriello Michal Valko SSL 97 30 0 06 Dec 2022
Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks Tilman Raukur A. Ho Stephen Casper Dylan Hadfield-Menell AAML AI4CE 95 133 0 27 Jul 2022
Live in the Moment: Learning Dynamics Model Adapted to Evolving Policy Xiyao Wang Wichayaporn Wongkamjan Furong Huang 71 19 0 25 Jul 2022
A Survey on Model-based Reinforcement Learning Fan Luo Tian Xu Hang Lai Xiong-Hui Chen Weinan Zhang Yang Yu OffRL LRM 98 106 0 19 Jun 2022
Control-Aware Prediction Objectives for Autonomous Driving R. McAllister Blake Wulfe Jean Mercat Logan Ellis Sergey Levine Adrien Gaidon 62 22 0 28 Apr 2022
Investigating Compounding Prediction Errors in Learned Dynamics Models Nathan Lambert K. Pister Roberto Calandra AI4CE 45 31 0 17 Mar 2022
Temporal Difference Learning for Model Predictive Control Nicklas Hansen Xiaolong Wang H. Su PINN MU 93 253 0 09 Mar 2022
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 298 30,149 0 01 Mar 2022
Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage Masatoshi Uehara Wen Sun OffRL 141 150 0 13 Jul 2021
Model-Advantage and Value-Aware Models for Model-Based Reinforcement Learning: Bridging the Gap in Theory and Practice Nirbhay Modhe Harish Kamath Dhruv Batra Ashwin Kalyan OffRL 29 2 0 26 Jun 2021
Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation Evgenii Nikishin Romina Abachi Rishabh Agarwal Pierre-Luc Bacon OffRL 86 37 0 06 Jun 2021
Minimax Model Learning Cameron Voloshin Nan Jiang Yisong Yue OffRL 112 18 0 02 Mar 2021
Towards Continual Reinforcement Learning: A Review and Perspectives Khimya Khetarpal Matthew D Riemer Irina Rish Doina Precup CLL OffRL 109 323 0 25 Dec 2020
Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning Nathan Lambert Albert Wilcox Howard Zhang K. Pister Roberto Calandra 62 33 0 16 Dec 2020
The Value Equivalence Principle for Model-Based Reinforcement Learning Christopher Grimm André Barreto Satinder Singh David Silver OffRL 49 85 0 06 Nov 2020
Generative Temporal Difference Learning for Infinite-Horizon Prediction Michael Janner Igor Mordatch Sergey Levine AI4CE 62 35 0 27 Oct 2020
Forethought and Hindsight in Credit Assignment Veronica Chelu Doina Precup H. V. Hasselt 76 26 0 26 Oct 2020
Error Bounds of Imitating Policies and Environments Tian Xu Ziniu Li Yang Yu 81 119 0 22 Oct 2020
Approximate information state for approximate planning and reinforcement learning in partially observed systems Jayakumar Subramanian Amit Sinha Raihan Seraj Aditya Mahajan 140 86 0 17 Oct 2020
Action and Perception as Divergence Minimization Danijar Hafner Pedro A. Ortega Jimmy Ba Thomas Parr Karl J. Friston N. Heess 74 53 0 03 Sep 2020
On the model-based stochastic value gradient for continuous reinforcement learning Brandon Amos Samuel Stanton Denis Yarats A. Wilson 67 71 0 28 Aug 2020
Data-Efficient Reinforcement Learning with Self-Predictive Representations Max Schwarzer Ankesh Anand Rishab Goel R. Devon Hjelm Aaron Courville Philip Bachman 93 321 0 12 Jul 2020
Learning Invariant Representations for Reinforcement Learning without Reconstruction Amy Zhang R. McAllister Roberto Calandra Y. Gal Sergey Levine OOD SSL 114 478 0 18 Jun 2020
Bootstrap your own latent: A new approach to self-supervised Learning Jean-Bastien Grill Florian Strub Florent Altché Corentin Tallec Pierre Harvey Richemond ... M. G. Azar Bilal Piot Koray Kavukcuoglu Rémi Munos Michal Valko SSL 395 6,837 0 13 Jun 2020
Variational Model-based Policy Optimization Yinlam Chow Brandon Cui Moonkyung Ryu Mohammad Ghavamzadeh OffRL 60 12 0 09 Jun 2020
Conservative Q-Learning for Offline Reinforcement Learning Aviral Kumar Aurick Zhou George Tucker Sergey Levine OffRL OnRL 143 1,831 0 08 Jun 2020
Deep active inference agents using Monte-Carlo methods Zafeirios Fountas Noor Sajid P. Mediano Karl J. Friston 80 106 0 07 Jun 2020
Model-Based Reinforcement Learning with Value-Targeted Regression Alex Ayoub Zeyu Jia Csaba Szepesvári Mengdi Wang Lin F. Yang OffRL 94 305 0 01 Jun 2020
MOReL : Model-Based Offline Reinforcement Learning Rahul Kidambi Aravind Rajeswaran Praneeth Netrapalli Thorsten Joachims OffRL 96 676 0 12 May 2020
Whence the Expected Free Energy? Beren Millidge Alexander Tschantz Christopher L. Buckley 48 69 0 17 Apr 2020
D4RL: Datasets for Deep Data-Driven Reinforcement Learning Justin Fu Aviral Kumar Ofir Nachum George Tucker Sergey Levine GP OffRL 229 1,381 0 15 Apr 2020
Objective Mismatch in Model-based Reinforcement Learning Nathan Lambert Brandon Amos Omry Yadan Roberto Calandra OffRL 44 97 0 11 Feb 2020
Dream to Control: Learning Behaviors by Latent Imagination Danijar Hafner Timothy Lillicrap Jimmy Ba Mohammad Norouzi VLM 126 1,371 0 03 Dec 2019
VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning L. Zintgraf K. Shiarlis Maximilian Igl Sebastian Schulze Y. Gal Katja Hofmann Shimon Whiteson OffRL 63 279 0 18 Oct 2019
The Differentiable Cross-Entropy Method Brandon Amos Denis Yarats 81 54 0 27 Sep 2019
ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots Michael Ahn Henry Zhu Kristian Hartikainen Hugo Ponte Abhishek Gupta Sergey Levine Vikash Kumar 63 130 0 25 Sep 2019
Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control Nir Levine Yinlam Chow Rui Shu Ang Li Mohammad Ghavamzadeh Hung Bui 48 30 0 04 Sep 2019
Learning Stabilizable Nonlinear Dynamics with Contraction-Based Regularization Sumeet Singh Spencer M. Richards Vikas Sindhwani Jean-Jacques E. Slotine Marco Pavone 80 75 0 29 Jul 2019
Deep Active Inference as Variational Policy Gradients Beren Millidge BDL 69 103 0 08 Jul 2019
When to Trust Your Model: Model-Based Policy Optimization Michael Janner Justin Fu Marvin Zhang Sergey Levine OffRL 102 956 0 19 Jun 2019
Soft Actor-Critic Algorithms and Applications Tuomas Haarnoja Aurick Zhou Kristian Hartikainen George Tucker Sehoon Ha ... Vikash Kumar Henry Zhu Abhishek Gupta Pieter Abbeel Sergey Levine 143 2,449 0 13 Dec 2018
Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review Sergey Levine AI4CE BDL 91 674 0 02 May 2018
Learning to Adapt in Dynamic, Real-World Environments Through Meta-Reinforcement Learning Anusha Nagabandi I. Clavera Simin Liu R. Fearing Pieter Abbeel Sergey Levine Chelsea Finn 130 553 0 30 Mar 2018
Addressing Function Approximation Error in Actor-Critic Methods Scott Fujimoto H. V. Hoof David Meger OffRL 187 5,212 0 26 Feb 2018
DeepMind Control Suite Yuval Tassa Yotam Doron Alistair Muldal Tom Erez Yazhe Li ... A. Abdolmaleki J. Merel Andrew Lefrancq Timothy Lillicrap Martin Riedmiller ELM LM&Ro BDL 148 1,143 0 02 Jan 2018
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm David Silver Thomas Hubert Julian Schrittwieser Ioannis Antonoglou Matthew Lai ... D. Kumaran T. Graepel Timothy Lillicrap Karen Simonyan Demis Hassabis 153 1,782 0 05 Dec 2017
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 532 19,265 0 20 Jul 2017
Value Prediction Network Junhyuk Oh Satinder Singh Honglak Lee 79 333 0 11 Jul 2017
Equivalence Between Policy Gradients and Soft Q-Learning John Schulman Xi Chen Pieter Abbeel OffRL 104 349 0 21 Apr 2017