Approximation Benefits of Policy Gradient Methods with Aggregated States

22 July 2020

Papers citing "Approximation Benefits of Policy Gradient Methods with Aggregated States"

26 / 26 papers shown

Title
Functional Acceleration for Policy Mirror Descent Veronica Chelu Doina Precup 44 0 0 23 Jul 2024
On the Linear convergence of Natural Policy Gradient Algorithm S. Khodadadian P. Jhunjhunwala Sushil Mahavir Varma S. T. Maguluri 66 57 0 04 May 2021
Sample Efficient Reinforcement Learning with REINFORCE Junzi Zhang Jongho Kim Brendan O'Donoghue Stephen P. Boyd 56 104 0 22 Oct 2020
On Linear Convergence of Policy Gradient Methods for Finite MDPs Jalaj Bhandari Daniel Russo 74 60 0 21 Jul 2020
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning Alekh Agarwal Mikael Henaff Sham Kakade Wen Sun OffRL 35 109 0 16 Jul 2020
On the Global Convergence Rates of Softmax Policy Gradient Methods Jincheng Mei Chenjun Xiao Csaba Szepesvári Dale Schuurmans 102 287 0 13 May 2020
Provably Efficient Reinforcement Learning with Aggregated States Shi Dong Benjamin Van Roy Zhengyuan Zhou 11 31 0 13 Dec 2019
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning Dipendra Kumar Misra Mikael Henaff A. Krishnamurthy John Langford 61 151 0 13 Nov 2019
On Connections between Constrained Optimization and Reinforcement Learning Nino Vieillard Olivier Pietquin Matthieu Geist 21 13 0 18 Oct 2019
Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs Lior Shani Yonathan Efroni Shie Mannor 40 175 0 06 Sep 2019
On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift Alekh Agarwal Sham Kakade Jason D. Lee G. Mahajan 46 320 0 01 Aug 2019
Global Optimality Guarantees For Policy Gradient Methods Jalaj Bhandari Daniel Russo 60 188 0 05 Jun 2019
State Aggregation Learning from Markov Transition Data Shiqi Wang Yizheng Chen Ahmed Abdou 54 54 0 06 Nov 2018
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 243 18,685 0 20 Jul 2017
Proximally Guided Stochastic Subgradient Method for Nonsmooth, Nonconvex Problems Damek Davis Benjamin Grimmer 35 112 0 12 Jul 2017
Equivalence Between Policy Gradients and Soft Q-Learning John Schulman Xi Chen Pieter Abbeel OffRL 64 344 0 21 Apr 2017
Near Optimal Behavior via Approximate State Abstraction David Abel D Ellis Hershkowitz Michael L. Littman OffRL 62 163 0 15 Jan 2017
Stochastic Frank-Wolfe Methods for Nonconvex Optimization Sashank J. Reddi S. Sra Barnabás Póczós Alex Smola 52 140 0 27 Jul 2016
Stochastic Variance Reduction for Nonconvex Optimization Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 80 598 0 19 Mar 2016
Trust Region Policy Optimization John Schulman Sergey Levine Philipp Moritz Michael I. Jordan Pieter Abbeel 245 6,722 0 19 Feb 2015
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 110 1,817 0 01 Jul 2014
Approximate Policy Iteration Schemes: A Comparison B. Scherrer 49 92 0 12 May 2014
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 140 738 0 19 Mar 2014
Least Squares Policy Iteration with Instrumental Variables vs. Direct Policy Search: Comparison Against Optimal Benchmarks Using Energy Storage Warren R. Scott Warrren B Powell Somayeh Moazehi 47 4 0 04 Jan 2014
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming Saeed Ghadimi Guanghui Lan ODL 90 1,538 0 22 Sep 2013
On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes B. Scherrer Boris Lesner OffRL 50 52 0 29 Nov 2012