Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation

24 March 2021

Papers citing "Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation"

48 / 48 papers shown

Title
Enhancing PPO with Trajectory-Aware Hybrid Policies Qisai Liu Zhanhong Jiang Hsin-Jung Yang Mahsa Khosravi Joshua R. Waite S. Sarkar 40 0 0 21 Feb 2025
A Model Selection Approach for Corruption Robust Reinforcement Learning Chen-Yu Wei Christoph Dann Julian Zimmert 77 44 0 31 Dec 2024
Dual Approximation Policy Optimization Zhihan Xiong Maryam Fazel Lin Xiao 15 1 0 02 Oct 2024
Leveraging Unlabeled Data Sharing through Kernel Function Approximation in Offline Reinforcement Learning Yen-Ru Lai Fu-Chieh Chang Pei-Yuan Wu OffRL 64 1 0 22 Aug 2024
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning Dake Zhang Boxiang Lyu Shuang Qiu Mladen Kolar Tong Zhang OffRL 25 0 0 10 Jul 2024
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization D. Tiapkin Evgenii Chzhen Gilles Stoltz 74 0 0 08 Jul 2024
Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions Noah Golowich Ankur Moitra OffRL 25 1 0 17 Jun 2024
Corruption-Robust Offline Two-Player Zero-Sum Markov Games Andi Nika Debmalya Mandal Adish Singla Goran Radanović OffRL 19 1 0 04 Mar 2024
Learning mirror maps in policy mirror descent Carlo Alfano Sebastian Towers Silvia Sapora Chris Xiaoxuan Lu Patrick Rebeschini 17 0 0 07 Feb 2024
Sample Complexity Characterization for Linear Contextual MDPs Junze Deng Yuan-Chia Cheng Shaofeng Zou Yingbin Liang 25 1 0 05 Feb 2024
Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-Constraint Wei Xiong Hanze Dong Chen Ye Ziqi Wang Han Zhong Heng Ji Nan Jiang Tong Zhang OffRL 36 155 0 18 Dec 2023
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback Canzhe Zhao Ruofeng Yang Baoxiang Wang Xuezhou Zhang Shuai Li 22 2 0 14 Nov 2023
Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback Haolin Liu Chen-Yu Wei Julian Zimmert 13 6 0 17 Oct 2023
Rate-Optimal Policy Optimization for Linear Markov Decision Processes Uri Sherman Alon Cohen Tomer Koren Yishay Mansour 23 7 0 28 Aug 2023
Provably Efficient Algorithm for Nonstationary Low-Rank MDPs Yuan-Chia Cheng J. Yang Yitao Liang OOD 25 1 0 10 Aug 2023
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations Ruiquan Huang Yitao Liang J. Yang OffRL 16 5 0 01 Jul 2023
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP Jiacheng Guo Zihao Li Huazheng Wang Mengdi Wang Zhuoran Yang Xuezhou Zhang 25 5 0 21 Jun 2023
On the Model-Misspecification in Reinforcement Learning Yunfan Li Lin F. Yang 28 5 0 19 Jun 2023
Low-Switching Policy Gradient with Exploration via Online Sensitivity Sampling Yunfan Li Yiran Wang Y. Cheng Lin F. Yang OffRL 16 4 0 15 Jun 2023
Improving Offline RL by Blending Heuristics Sinong Geng Aldo Pacchiano Andrey Kolobov Ching-An Cheng OffRL 17 7 0 01 Jun 2023
Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL Qinghua Liu Gellert Weisz András Gyorgy Chi Jin Csaba Szepesvári OffRL 16 8 0 18 May 2023
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes Han Zhong Tong Zhang 17 26 0 15 May 2023
Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs Yuan-Chia Cheng Ruiquan Huang J. Yang Yitao Liang OffRL 37 8 0 20 Mar 2023
Best of Both Worlds Policy Optimization Christoph Dann Chen-Yu Wei Julian Zimmert 11 12 0 18 Feb 2023
A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence Carlo Alfano Rui Yuan Patrick Rebeschini 54 15 0 30 Jan 2023
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation Uri Sherman Tomer Koren Yishay Mansour 9 12 0 30 Jan 2023
Refined Regret for Adversarial MDPs with Linear Function Approximation Yan Dai Haipeng Luo Chen-Yu Wei Julian Zimmert 16 12 0 30 Jan 2023
Sample Efficient Deep Reinforcement Learning via Local Planning Dong Yin S. Thiagarajan N. Lazić Nived Rajaraman Botao Hao Csaba Szepesvári 13 4 0 29 Jan 2023
Latent Variable Representation for Reinforcement Learning Tongzheng Ren Chenjun Xiao Tianjun Zhang Na Li Zhaoran Wang Sujay Sanghavi Dale Schuurmans Bo Dai OffRL 11 10 0 17 Dec 2022
CIM: Constrained Intrinsic Motivation for Sparse-Reward Continuous Control Xiang Zheng Xingjun Ma Cong Wang 16 1 0 28 Nov 2022
Linear Convergence for Natural Policy Gradient with Log-linear Policy Parametrization Carlo Alfano Patrick Rebeschini 49 13 0 30 Sep 2022
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning Shuang Qiu Lingxiao Wang Chenjia Bai Zhuoran Yang Zhaoran Wang SSL OffRL 8 32 0 29 Jul 2022
Convergence and sample complexity of natural policy gradient primal-dual methods for constrained MDPs Dongsheng Ding K. Zhang Jiali Duan Tamer Bacsar Mihailo R. Jovanović 13 19 0 06 Jun 2022
Stabilizing Q-learning with Linear Architectures for Provably Efficient Learning Andrea Zanette Martin J. Wainwright OOD 19 5 0 01 Jun 2022
Provable Benefits of Representational Transfer in Reinforcement Learning Alekh Agarwal Yuda Song Wen Sun Kaiwen Wang Mengdi Wang Xuezhou Zhang OffRL 16 33 0 29 May 2022
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning Approach Xuezhou Zhang Yuda Song Masatoshi Uehara Mengdi Wang Alekh Agarwal Wen Sun OffRL 11 57 0 31 Jan 2022
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee Tianhao Wu Yunchang Yang Han Zhong Liwei Wang S. Du Jiantao Jiao 23 14 0 21 Dec 2021
On the Global Optimum Convergence of Momentum-based Policy Gradient Yuhao Ding Junzi Zhang Javad Lavaei 17 16 0 19 Oct 2021
Representation Learning for Online and Offline RL in Low-rank MDPs Masatoshi Uehara Xuezhou Zhang Wen Sun OffRL 25 125 0 09 Oct 2021
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning Andrea Zanette Martin J. Wainwright Emma Brunskill OffRL 11 111 0 19 Aug 2021
Efficient Local Planning with Linear Function Approximation Dong Yin Botao Hao Yasin Abbasi-Yadkori N. Lazić Csaba Szepesvári 27 18 0 12 Aug 2021
Design of Experiments for Stochastic Contextual Linear Bandits Andrea Zanette Kefan Dong Jonathan Lee Emma Brunskill OffRL 17 17 0 21 Jul 2021
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses Haipeng Luo Chen-Yu Wei Chung-Wei Lee 14 44 0 18 Jul 2021
MADE: Exploration via Maximizing Deviation from Explored Regions Tianjun Zhang Paria Rashidinejad Jiantao Jiao Yuandong Tian Joseph E. Gonzalez Stuart J. Russell OffRL 13 42 0 18 Jun 2021
Corruption-Robust Offline Reinforcement Learning Xuezhou Zhang Yiding Chen Jerry Zhu Wen Sun OffRL 18 39 0 11 Jun 2021
Navigating to the Best Policy in Markov Decision Processes Aymen Al Marjani Aurélien Garivier Alexandre Proutière 14 20 0 05 Jun 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 107 166 0 06 Jan 2021
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 127 135 0 09 Dec 2019