A Theory of Regularized Markov Decision Processes

31 January 2019

Olivier Pietquin

Papers citing "A Theory of Regularized Markov Decision Processes"

41 / 91 papers shown

Title
Dimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning Carlo Alfano Patrick Rebeschini 50 5 0 23 Sep 2021
A Survey of Exploration Methods in Reinforcement Learning Susan Amin Maziar Gomrokchi Harsh Satija H. V. Hoof Doina Precup OffRL 39 80 0 01 Sep 2021
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning Andrea Zanette Martin J. Wainwright Emma Brunskill OffRL 34 115 0 19 Aug 2021
Implicitly Regularized RL with Implicit Q-Values Nino Vieillard Marcin Andrychowicz Anton Raichuk Olivier Pietquin M. Geist OffRL 24 9 0 16 Aug 2021
Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences Alan Chan Hugo Silva Sungsu Lim Tadashi Kozuno A. R. Mahmood Martha White 25 29 0 17 Jul 2021
Bellman-consistent Pessimism for Offline Reinforcement Learning Tengyang Xie Ching-An Cheng Nan Jiang Paul Mineiro Alekh Agarwal OffRL LRM 29 271 0 13 Jun 2021
Offline Reinforcement Learning as Anti-Exploration Shideh Rezaeifar Robert Dadashi Nino Vieillard Léonard Hussenot Olivier Bachem Olivier Pietquin M. Geist OffRL 54 51 0 11 Jun 2021
Concave Utility Reinforcement Learning: the Mean-Field Game Viewpoint M. Geist Julien Pérolat Mathieu Laurière Romuald Elie Sarah Perrin Olivier Bachem Rémi Munos Olivier Pietquin 42 63 0 07 Jun 2021
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization Shicong Cen Yuting Wei Yuejie Chi 39 77 0 31 May 2021
Finite-Sample Analysis of Off-Policy Natural Actor-Critic with Linear Function Approximation Zaiwei Chen S. Khodadadian S. T. Maguluri OffRL 68 29 0 26 May 2021
Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence Wenhao Zhan Shicong Cen Baihe Huang Yuxin Chen Jason D. Lee Yuejie Chi 32 76 0 24 May 2021
Reinforcement learning of rare diffusive dynamics Avishek Das Dominic C. Rose J. P. Garrahan David T. Limmer 24 27 0 10 May 2021
On the Linear convergence of Natural Policy Gradient Algorithm S. Khodadadian P. Jhunjhunwala Sushil Mahavir Varma S. T. Maguluri 45 56 0 04 May 2021
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation Andrea Zanette Ching-An Cheng Alekh Agarwal 37 53 0 24 Mar 2021
Near Optimal Policy Optimization via REPS Aldo Pacchiano Jonathan Lee Peter L. Bartlett Ofir Nachum 23 3 0 17 Mar 2021
Maximum Entropy RL (Provably) Solves Some Robust RL Problems Benjamin Eysenbach Sergey Levine OOD 50 176 0 10 Mar 2021
Dealing with Non-Stationarity in MARL via Trust-Region Decomposition Wenhao Li Xiangfeng Wang Bo Jin Junjie Sheng H. Zha 36 7 0 21 Feb 2021
Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm S. Khodadadian Zaiwei Chen S. T. Maguluri CML OffRL 74 26 0 18 Feb 2021
Online Apprenticeship Learning Lior Shani Tom Zahavy Shie Mannor OffRL 31 25 0 13 Feb 2021
Logistic Q-Learning Joan Bas-Serrano Sebastian Curi Andreas Krause Gergely Neu 14 40 0 21 Oct 2020
Revisiting Design Choices in Proximal Policy Optimization Chloe Ching-Yun Hsu Celestine Mendler-Dünner Moritz Hardt 25 53 0 23 Sep 2020
Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy Zuyue Fu Zhuoran Yang Zhaoran Wang 26 42 0 02 Aug 2020
Monte-Carlo Tree Search as Regularized Policy Optimization Jean-Bastien Grill Florent Altché Yunhao Tang Thomas Hubert Michal Valko Ioannis Antonoglou Rémi Munos 29 73 0 24 Jul 2020
On Linear Convergence of Policy Gradient Methods for Finite MDPs Jalaj Bhandari Daniel Russo 59 59 0 21 Jul 2020
Provably Good Batch Reinforcement Learning Without Great Exploration Yao Liu Adith Swaminathan Alekh Agarwal Emma Brunskill OffRL 27 105 0 16 Jul 2020
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity Kai Zhang Sham Kakade Tamer Bacsar Lin F. Yang 52 120 0 15 Jul 2020
Sparse Randomized Shortest Paths Routing with Tsallis Divergence Regularization P. Leleux Sylvain Courtain Guillaume Guex M. Saerens OT 24 5 0 01 Jul 2020
Gradient Flows for Regularized Stochastic Control Problems David Siska Lukasz Szpruch 31 20 0 10 Jun 2020
Mirror Descent Policy Optimization Manan Tomar Lior Shani Yonathan Efroni Mohammad Ghavamzadeh 30 83 0 20 May 2020
Scalable First-Order Methods for Robust MDPs Julien Grand-Clément Christian Kroer 24 28 0 11 May 2020
Leverage the Average: an Analysis of KL Regularization in RL Nino Vieillard Tadashi Kozuno B. Scherrer Olivier Pietquin Rémi Munos M. Geist 27 43 0 31 Mar 2020
Stable Policy Optimization via Off-Policy Divergence Regularization Ahmed Touati Amy Zhang Joelle Pineau Pascal Vincent OffRL 36 17 0 09 Mar 2020
Adaptive Approximate Policy Iteration Botao Hao N. Lazić Yasin Abbasi-Yadkori Pooria Joulani Csaba Szepesvári 18 14 0 08 Feb 2020
On Connections between Constrained Optimization and Reinforcement Learning Nino Vieillard Olivier Pietquin M. Geist 14 13 0 18 Oct 2019
Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning? S. Du Sham Kakade Ruosong Wang Lin F. Yang 47 192 0 07 Oct 2019
On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift Alekh Agarwal Sham Kakade Jason D. Lee G. Mahajan 13 316 0 01 Aug 2019
On the Convergence of Model Free Learning in Mean Field Games Romuald Elie Julien Pérolat Mathieu Laurière M. Geist Olivier Pietquin 38 89 0 04 Jul 2019
Modified Actor-Critics Erinc Merdivan S. Hanke M. Geist 24 2 0 02 Jul 2019
Global Optimality Guarantees For Policy Gradient Methods Jalaj Bhandari Daniel Russo 41 186 0 05 Jun 2019
A Theoretical Analysis of Deep Q-Learning Jianqing Fan Zhuoran Yang Yuchen Xie Zhaoran Wang 30 597 0 01 Jan 2019
VIREL: A Variational Inference Framework for Reinforcement Learning M. Fellows Anuj Mahajan Tim G. J. Rudner Shimon Whiteson DRL 38 54 0 03 Nov 2018