Lipschitz Continuity in Model-based Reinforcement Learning

19 April 2018

Michael L. Littman

Papers citing "Lipschitz Continuity in Model-based Reinforcement Learning"

38 / 88 papers shown

Title
Mismatched No More: Joint Model-Policy Optimization for Model-Based RL Benjamin Eysenbach Alexander Khazatsky Sergey Levine Ruslan Salakhutdinov OffRL 206 44 0 06 Oct 2021
Adversarially Regularized Policy Learning Guided by Trajectory Optimization Zhigen Zhao Simiao Zuo T. Zhao Ye Zhao 28 10 0 16 Sep 2021
Learning Markov State Abstractions for Deep Reinforcement Learning Cameron Allen Neev Parikh Omer Gottesman George Konidaris BDL OffRL 31 36 0 08 Jun 2021
Efficient Sampling in POMDPs with Lipschitz Bandits for Motion Planning in Continuous Spaces Omer Sahin Tas Felix Hauser Martin Lauer 11 3 0 08 Jun 2021
Fundamental Challenges in Deep Learning for Stiff Contact Dynamics Mihir Parmar Mathew Halm Michael Posa 29 36 0 29 Mar 2021
NRTSI: Non-Recurrent Time Series Imputation Siyuan Shan Yang Li Junier B. Oliva AI4TS 21 36 0 05 Feb 2021
Error Bounds of Imitating Policies and Environments Tian Xu Ziniu Li Yang Yu 28 118 0 22 Oct 2020
Model-based Policy Optimization with Unsupervised Model Adaptation Jian Shen Han Zhao Weinan Zhang Yong Yu 30 27 0 19 Oct 2020
Approximate information state for approximate planning and reinforcement learning in partially observed systems Jayakumar Subramanian Amit Sinha Raihan Seraj Aditya Mahajan 11 78 0 17 Oct 2020
Enhancing Mixup-based Semi-Supervised Learning with Explicit Lipschitz Regularization P. Gyawali S. Ghimire Linwei Wang AAML 36 7 0 23 Sep 2020
Complex Robotic Manipulation via Graph-Based Hindsight Goal Generation Zhenshan Bing Matthias Brucker F. O. Morin Kai-Qi Huang Alois C. Knoll 19 27 0 27 Jul 2020
Bidirectional Model-based Policy Optimization Hang Lai Jian Shen Weinan Zhang Yong Yu 17 57 0 04 Jul 2020
Model Embedding Model-Based Reinforcement Learning Xiao Tan C. Qu Junwu Xiong James Y. Zhang OffRL 16 0 0 16 Jun 2020
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis Weichao Mao Kaipeng Zhang Qiaomin Xie Tamer Basar 19 14 0 08 Jun 2020
Zooming for Efficient Model-Free Reinforcement Learning in Metric Spaces Ahmed Touati Adrien Ali Taïga Marc G. Bellemare 11 19 0 09 Mar 2020
Neural Lyapunov Model Predictive Control: Learning Safe Global Controllers from Sub-optimal Examples Mayank Mittal Marco Gallieri A. Quaglino Seyed Sina Mirrazavi Salehian Jan Koutník 12 10 0 21 Feb 2020
Mean-Field Controls with Q-learning for Cooperative MARL: Convergence and Complexity Analysis Haotian Gu Xin Guo Xiaoli Wei Renyuan Xu 32 65 0 10 Feb 2020
Deep Radial-Basis Value Functions for Continuous Control Kavosh Asadi Neev Parikh Ronald E. Parr George Konidaris Michael L. Littman 25 4 0 05 Feb 2020
Lipschitz Lifelong Reinforcement Learning Erwan Lecarpentier David Abel Kavosh Asadi Yuu Jinnai Emmanuel Rachelson Michael L. Littman OffRL CLL 8 39 0 15 Jan 2020
Learning to Combat Compounding-Error in Model-Based Reinforcement Learning Chenjun Xiao Yifan Wu Chen Ma Dale Schuurmans Martin Müller OffRL 11 43 0 24 Dec 2019
Observational Overfitting in Reinforcement Learning Xingyou Song Yiding Jiang Stephen Tu Yilun Du Behnam Neyshabur OffRL 33 138 0 06 Dec 2019
Learning to Predict Without Looking Ahead: World Models Without Forward Prediction C. Freeman Luke Metz David R Ha 33 35 0 29 Oct 2019
Wasserstein Robust Reinforcement Learning Mohammed Abdullah Hang Ren Haitham Bou-Ammar Vladimir Milenkovic Rui Luo Mingtian Zhang Jun Wang 32 75 0 30 Jul 2019
Dreaming machine learning: Lipschitz extensions for reinforcement learning on financial markets J. Calabuig H. Falciani E. A. Sánchez-Pérez 13 26 0 09 Jul 2019
When to Trust Your Model: Model-Based Policy Optimization Michael Janner Justin Fu Marvin Zhang Sergey Levine OffRL 16 931 0 19 Jun 2019
Exploration via Hindsight Goal Generation Zhizhou Ren Kefan Dong Yuanshuo Zhou Qiang Liu Jian-wei Peng 35 85 0 10 Jun 2019
DeepMDP: Learning Continuous Latent Space Models for Representation Learning Carles Gelada Saurabh Kumar Jacob Buckman Ofir Nachum Marc G. Bellemare BDL 14 279 0 06 Jun 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
Combining Parametric and Nonparametric Models for Off-Policy Evaluation Omer Gottesman Yao Liu Scott Sussex Emma Brunskill Finale Doshi-Velez OffRL 17 33 0 14 May 2019
Non-Stationary Markov Decision Processes, a Worst-Case Approach using Model-Based Reinforcement Learning, Extended version Erwan Lecarpentier Emmanuel Rachelson 10 82 0 22 Apr 2019
Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future Nan Rosemary Ke Amanpreet Singh Ahmed Touati Anirudh Goyal Yoshua Bengio Devi Parikh Dhruv Batra 29 48 0 05 Mar 2019
Successor Features Combine Elements of Model-Free and Model-based Reinforcement Learning Lucas Lehnert Michael L. Littman 16 10 0 31 Jan 2019
An investigation of model-free planning A. Guez M. Berk Mirza Karol Gregor Rishabh Kabra S. Racanière ... Laurent Orseau Tom Eccles Greg Wayne David Silver Timothy Lillicrap OffRL 30 111 0 11 Jan 2019
Towards a Simple Approach to Multi-step Model-based Reinforcement Learning Kavosh Asadi Evan Cater Dipendra Kumar Misra Michael L. Littman OffRL 24 13 0 31 Oct 2018
Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees Yuping Luo Huazhe Xu Yuanzhi Li Yuandong Tian Trevor Darrell Tengyu Ma OffRL 55 223 0 10 Jul 2018
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control Yangchen Pan Amir-massoud Farahmand Martha White S. Nabi P. Grover D. Nikovski 51 18 0 13 Jun 2018
Equivalence Between Wasserstein and Value-Aware Loss for Model-based Reinforcement Learning Kavosh Asadi Evan Cater Dipendra Kumar Misra Michael L. Littman OffRL 13 11 0 01 Jun 2018
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 127 577 0 27 Feb 2015