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Policy Mirror Descent Inherently Explores Action Space

8 March 2023

Papers citing "Policy Mirror Descent Inherently Explores Action Space"

21 / 21 papers shown

Title
First-order Policy Optimization for Robust Markov Decision Process Yan Li Guanghui Lan Tuo Zhao 149 25 0 21 Sep 2022
Stochastic first-order methods for average-reward Markov decision processes Tianjiao Li Feiyang Wu Guanghui Lan 64 14 0 11 May 2022
Stochastic linear optimization never overfits with quadratically-bounded losses on general data Matus Telgarsky 64 12 0 14 Feb 2022
Block Policy Mirror Descent Guanghui Lan Yan Li T. Zhao OffRL 61 10 0 15 Jan 2022
Actor-critic is implicitly biased towards high entropy optimal policies Yuzheng Hu Ziwei Ji Matus Telgarsky 90 11 0 21 Oct 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 69 78 0 24 May 2021
Provably Correct Optimization and Exploration with Non-linear Policies Fei Feng W. Yin Alekh Agarwal Lin F. Yang 138 13 0 22 Mar 2021
Policy Mirror Descent for Reinforcement Learning: Linear Convergence, New Sampling Complexity, and Generalized Problem Classes Guanghui Lan 184 143 0 30 Jan 2021
Finite Sample Analysis of Two-Time-Scale Natural Actor-Critic Algorithm S. Khodadadian Thinh T. Doan Justin Romberg S. T. Maguluri 85 43 0 26 Jan 2021
Simple and optimal methods for stochastic variational inequalities, II: Markovian noise and policy evaluation in reinforcement learning Georgios Kotsalis Guanghui Lan Tianjiao Li OffRL 57 32 0 15 Nov 2020
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning Alekh Agarwal Mikael Henaff Sham Kakade Wen Sun OffRL 78 110 0 16 Jul 2020
Optimistic Policy Optimization with Bandit Feedback Yonathan Efroni Lior Shani Aviv A. Rosenberg Shie Mannor 61 90 0 19 Feb 2020
Provably Efficient Exploration in Policy Optimization Qi Cai Zhuoran Yang Chi Jin Zhaoran Wang 83 283 0 12 Dec 2019
Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs Lior Shani Yonathan Efroni Shie Mannor 60 176 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 72 321 0 01 Aug 2019
Tsallis Reinforcement Learning: A Unified Framework for Maximum Entropy Reinforcement Learning Kyungjae Lee Sungyub Kim Sungbin Lim Sungjoon Choi Songhwai Oh 131 28 0 31 Jan 2019
Is Q-learning Provably Efficient? Chi Jin Zeyuan Allen-Zhu Sébastien Bubeck Michael I. Jordan OffRL 81 812 0 10 Jul 2018
A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation Jalaj Bhandari Daniel Russo Raghav Singal 113 340 0 06 Jun 2018
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 550 19,296 0 20 Jul 2017
Minimax Regret Bounds for Reinforcement Learning M. G. Azar Ian Osband Rémi Munos 95 778 0 16 Mar 2017
Trust Region Policy Optimization John Schulman Sergey Levine Philipp Moritz Michael I. Jordan Pieter Abbeel 281 6,801 0 19 Feb 2015