Model-based RL with Optimistic Posterior Sampling: Structural Conditions
and Sample Complexity

Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity

15 June 2022

Tong Zhang

Papers citing "Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity"

19 / 19 papers shown

Title
Satisficing Exploration for Deep Reinforcement Learning Dilip Arumugam Saurabh Kumar Ramki Gummadi Benjamin Van Roy 32 0 0 16 Jul 2024
More Efficient Randomized Exploration for Reinforcement Learning via Approximate Sampling Haque Ishfaq Yixin Tan Yu Yang Qingfeng Lan Jianfeng Lu A. Rupam Mahmood Doina Precup Pan Xu 32 4 0 18 Jun 2024
Feel-Good Thompson Sampling for Contextual Dueling Bandits Xuheng Li Heyang Zhao Quanquan Gu 40 8 0 09 Apr 2024
Regret Minimization via Saddle Point Optimization Johannes Kirschner Seyed Alireza Bakhtiari Kushagra Chandak Volodymyr Tkachuk Csaba Szepesvári 26 1 0 15 Mar 2024
Optimistic Information Directed Sampling Gergely Neu Matteo Papini Ludovic Schwartz 37 2 0 23 Feb 2024
Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption Chen Ye Jiafan He Quanquan Gu Tong Zhang 35 5 0 14 Feb 2024
Optimistic Thompson Sampling for No-Regret Learning in Unknown Games Yingru Li Liangqi Liu Wenqiang Pu Hao Liang Zhi-Quan Luo 21 2 0 07 Feb 2024
Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes Ruiquan Huang Yuan-Chia Cheng Jing Yang Vincent Tan Yingbin Liang 19 0 0 20 Oct 2023
Sample-Efficient Multi-Agent RL: An Optimization Perspective Nuoya Xiong Zhihan Liu Zhaoran Wang Zhuoran Yang 36 1 0 10 Oct 2023
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning Qiwei Di Heyang Zhao Jiafan He Quanquan Gu OffRL 37 5 0 02 Oct 2023
Bayesian Design Principles for Frequentist Sequential Learning Yunbei Xu A. Zeevi 16 11 0 01 Oct 2023
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight Jiacheng Guo Minshuo Chen Haiquan Wang Caiming Xiong Mengdi Wang Yu Bai 8 5 0 06 Jul 2023
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations Ruiquan Huang Yitao Liang J. Yang OffRL 16 5 0 01 Jul 2023
Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration Zhihan Liu Miao Lu Wei Xiong Han Zhong Haotian Hu Shenao Zhang Sirui Zheng Zhuoran Yang Zhaoran Wang OffRL 32 22 0 29 May 2023
Bridging Imitation and Online Reinforcement Learning: An Optimistic Tale Botao Hao Rahul Jain Dengwang Tang Zheng Wen OffRL 19 2 0 20 Mar 2023
Learning in POMDPs is Sample-Efficient with Hindsight Observability Jonathan Lee Alekh Agarwal Christoph Dann Tong Zhang 18 19 0 31 Jan 2023
Model-Free Reinforcement Learning with the Decision-Estimation Coefficient Dylan J. Foster Noah Golowich Jian Qian Alexander Rakhlin Ayush Sekhari OffRL 22 9 0 25 Nov 2022
Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms Fan Chen Yu Bai Song Mei 53 22 0 29 Sep 2022
Deep Dynamics Models for Learning Dexterous Manipulation Anusha Nagabandi K. Konolige Sergey Levine Vikash Kumar 143 407 0 25 Sep 2019