Self-Correcting Models for Model-Based Reinforcement Learning

19 December 2016

Papers citing "Self-Correcting Models for Model-Based Reinforcement Learning"

23 / 23 papers shown

Title
Model-Based Offline Reinforcement Learning with Reliability-Guaranteed Sequence Modeling Shenghong He OffRL 266 0 0 10 Feb 2025
On-line Policy Improvement using Monte-Carlo Search Gerald Tesauro Gregory R. Galperin 92 270 0 09 Jan 2025
Meta-Gradient Search Control: A Method for Improving the Efficiency of Dyna-style Planning Bradley Burega John D. Martin Luke Kapeluck Michael Bowling 40 0 0 27 Jun 2024
A Note on Loss Functions and Error Compounding in Model-based Reinforcement Learning Nan Jiang 43 5 0 15 Apr 2024
A Tractable Inference Perspective of Offline RL Xuejie Liu Hoang Trung-Dung Guy Van den Broeck Yitao Liang OffRL 36 1 0 31 Oct 2023
$λ$ -models: Effective Decision-Aware Reinforcement Learning with Latent Models C. Voelcker Arash Ahmadian Romina Abachi Igor Gilitschenski Amir-massoud Farahmand 59 0 0 30 Jun 2023
Off-Policy RL Algorithms Can be Sample-Efficient for Continuous Control via Sample Multiple Reuse Jiafei Lyu Le Wan Zongqing Lu Xiu Li OffRL 36 9 0 29 May 2023
Reward-Predictive Clustering Lucas Lehnert M. Frank Michael L. Littman OffRL 27 0 0 07 Nov 2022
Goal-Space Planning with Subgoal Models Chun-Ping Lo Kevin Roice Parham Mohammad Panahi Scott M. Jordan Adam White Gábor Mihucz Farzane Aminmansour Martha White 29 5 0 06 Jun 2022
Temporally Abstract Partial Models Khimya Khetarpal Zafarali Ahmed Gheorghe Comanici Doina Precup 26 14 0 06 Aug 2021
High-dimensional separability for one- and few-shot learning Alexander N. Gorban Bogdan Grechuk Evgeny M. Mirkes Sergey V. Stasenko I. Tyukin DRL 42 20 0 28 Jun 2021
Learning One Representation to Optimize All Rewards Ahmed Touati Yann Ollivier OffRL 21 60 0 14 Mar 2021
Generative Temporal Difference Learning for Infinite-Horizon Prediction Michael Janner Igor Mordatch Sergey Levine AI4CE 23 34 0 27 Oct 2020
Model-based Policy Optimization with Unsupervised Model Adaptation Jian Shen Han Zhao Weinan Zhang Yong Yu 37 27 0 19 Oct 2020
Dynamic Horizon Value Estimation for Model-based Reinforcement Learning Junjie Wang Qichao Zhang Dongbin Zhao Mengchen Zhao Jianye Hao OffRL 32 5 0 21 Sep 2020
Selective Dyna-style Planning Under Limited Model Capacity Zaheer Abbas Samuel Sokota Erin J. Talvitie Martha White 43 32 0 05 Jul 2020
Data Efficient Reinforcement Learning for Legged Robots Yuxiang Yang Ken Caluwaerts Atil Iscen Tingnan Zhang Jie Tan Vikas Sindhwani 33 139 0 08 Jul 2019
Combating the Compounding-Error Problem with a Multi-step Model Kavosh Asadi Dipendra Kumar Misra Seungchan Kim Michel L. Littman LRM 16 55 0 30 May 2019
Successor Features Combine Elements of Model-Free and Model-based Reinforcement Learning Lucas Lehnert Michael L. Littman 29 10 0 31 Jan 2019
Towards a Simple Approach to Multi-step Model-based Reinforcement Learning Kavosh Asadi Evan Cater Dipendra Kumar Misra Michael L. Littman OffRL 29 13 0 31 Oct 2018
Lipschitz Continuity in Model-based Reinforcement Learning Kavosh Asadi Dipendra Kumar Misra Michael L. Littman KELM 43 150 0 19 Apr 2018
TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning Gregory Farquhar Tim Rocktaschel Maximilian Igl Shimon Whiteson OffRL 25 71 0 31 Oct 2017
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents Marlos C. Machado Marc G. Bellemare Erik Talvitie J. Veness Matthew J. Hausknecht Michael Bowling 37 544 0 18 Sep 2017