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Learning Near Optimal Policies with Low Inherent Bellman Error
v1v2v3 (latest)

Learning Near Optimal Policies with Low Inherent Bellman Error

29 February 2020
Andrea Zanette
A. Lazaric
Mykel Kochenderfer
Emma Brunskill
    OffRL
ArXiv (abs)PDFHTML

Papers citing "Learning Near Optimal Policies with Low Inherent Bellman Error"

50 / 94 papers shown
Title
Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
Uri Sherman
Tomer Koren
Yishay Mansour
46
0
0
16 Feb 2025
A Model Selection Approach for Corruption Robust Reinforcement Learning
A Model Selection Approach for Corruption Robust Reinforcement Learning
Chen-Yu Wei
Christoph Dann
Julian Zimmert
195
45
0
31 Dec 2024
On Sample-Efficient Offline Reinforcement Learning: Data Diversity,
  Posterior Sampling, and Beyond
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond
Thanh Nguyen-Tang
Raman Arora
OffRL
95
3
0
06 Jan 2024
Provable Benefits of Multi-task RL under Non-Markovian Decision Making
  Processes
Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes
Ruiquan Huang
Yuan Cheng
Jing Yang
Vincent Tan
Yingbin Liang
75
0
0
20 Oct 2023
Uncertainty-aware transfer across tasks using hybrid model-based
  successor feature reinforcement learning
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning
Parvin Malekzadeh
Ming Hou
Konstantinos N. Plataniotis
92
1
0
16 Oct 2023
Kernelized Reinforcement Learning with Order Optimal Regret Bounds
Kernelized Reinforcement Learning with Order Optimal Regret Bounds
Sattar Vakili
Julia Olkhovskaya
103
9
0
13 Jun 2023
Provable and Practical: Efficient Exploration in Reinforcement Learning
  via Langevin Monte Carlo
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo
Haque Ishfaq
Qingfeng Lan
Pan Xu
A. R. Mahmood
Doina Precup
Anima Anandkumar
Kamyar Azizzadenesheli
BDLOffRL
114
23
0
29 May 2023
Reinforcement Learning with Delayed, Composite, and Partially Anonymous
  Reward
Reinforcement Learning with Delayed, Composite, and Partially Anonymous Reward
Washim Uddin Mondal
Vaneet Aggarwal
83
2
0
04 May 2023
Provably Feedback-Efficient Reinforcement Learning via Active Reward
  Learning
Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning
Dingwen Kong
Lin F. Yang
99
12
0
18 Apr 2023
Does Sparsity Help in Learning Misspecified Linear Bandits?
Does Sparsity Help in Learning Misspecified Linear Bandits?
Jialin Dong
Lin F. Yang
70
1
0
29 Mar 2023
On the Interplay Between Misspecification and Sub-optimality Gap in
  Linear Contextual Bandits
On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits
Weitong Zhang
Jiafan He
Zhiyuan Fan
Q. Gu
145
5
0
16 Mar 2023
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement
  Learning: Adaptivity and Computational Efficiency
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency
Heyang Zhao
Jiafan He
Dongruo Zhou
Tong Zhang
Quanquan Gu
101
28
0
21 Feb 2023
Reinforcement Learning with Function Approximation: From Linear to
  Nonlinear
Reinforcement Learning with Function Approximation: From Linear to Nonlinear
Jihao Long
Jiequn Han
70
6
0
20 Feb 2023
Near-optimal Policy Identification in Active Reinforcement Learning
Near-optimal Policy Identification in Active Reinforcement Learning
Xiang Li
Viraj Mehta
Johannes Kirschner
I. Char
Willie Neiswanger
J. Schneider
Andreas Krause
Ilija Bogunovic
OffRL
85
6
0
19 Dec 2022
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision
  Processes
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes
Jiafan He
Heyang Zhao
Dongruo Zhou
Quanquan Gu
OffRL
136
55
0
12 Dec 2022
Model-Free Reinforcement Learning with the Decision-Estimation
  Coefficient
Model-Free Reinforcement Learning with the Decision-Estimation Coefficient
Dylan J. Foster
Noah Golowich
Jian Qian
Alexander Rakhlin
Ayush Sekhari
OffRL
94
10
0
25 Nov 2022
Leveraging Offline Data in Online Reinforcement Learning
Leveraging Offline Data in Online Reinforcement Learning
Andrew Wagenmaker
Aldo Pacchiano
OffRLOnRL
103
41
0
09 Nov 2022
Confident Approximate Policy Iteration for Efficient Local Planning in
  $q^π$-realizable MDPs
Confident Approximate Policy Iteration for Efficient Local Planning in qπq^πqπ-realizable MDPs
Gellert Weisz
András Gyorgy
Tadashi Kozuno
Csaba Szepesvári
78
7
0
27 Oct 2022
Efficient Global Planning in Large MDPs via Stochastic Primal-Dual
  Optimization
Efficient Global Planning in Large MDPs via Stochastic Primal-Dual Optimization
Gergely Neu
Nneka Okolo
108
7
0
21 Oct 2022
A Reinforcement Learning Approach in Multi-Phase Second-Price Auction
  Design
A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design
Rui Ai
Boxiang Lyu
Zhaoran Wang
Zhuoran Yang
Michael I. Jordan
78
3
0
19 Oct 2022
Hybrid RL: Using Both Offline and Online Data Can Make RL Efficient
Hybrid RL: Using Both Offline and Online Data Can Make RL Efficient
Yuda Song
Yi Zhou
Ayush Sekhari
J. Andrew Bagnell
A. Krishnamurthy
Wen Sun
OffRLOnRL
94
105
0
13 Oct 2022
The Role of Coverage in Online Reinforcement Learning
The Role of Coverage in Online Reinforcement Learning
Tengyang Xie
Dylan J. Foster
Yu Bai
Nan Jiang
Sham Kakade
OffRL
85
60
0
09 Oct 2022
Offline Reinforcement Learning with Differentiable Function
  Approximation is Provably Efficient
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient
Ming Yin
Mengdi Wang
Yu Wang
OffRL
141
12
0
03 Oct 2022
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning
  with Linear Function Approximation
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation
Dan Qiao
Yu Wang
OffRL
123
13
0
03 Oct 2022
A General Framework for Sample-Efficient Function Approximation in
  Reinforcement Learning
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
Zixiang Chen
C. J. Li
An Yuan
Quanquan Gu
Michael I. Jordan
OffRL
151
27
0
30 Sep 2022
Understanding Deep Neural Function Approximation in Reinforcement
  Learning via $ε$-Greedy Exploration
Understanding Deep Neural Function Approximation in Reinforcement Learning via εεε-Greedy Exploration
Fanghui Liu
Luca Viano
Volkan Cevher
116
19
0
15 Sep 2022
Future-Dependent Value-Based Off-Policy Evaluation in POMDPs
Future-Dependent Value-Based Off-Policy Evaluation in POMDPs
Masatoshi Uehara
Haruka Kiyohara
Andrew Bennett
Victor Chernozhukov
Nan Jiang
Nathan Kallus
C. Shi
Wen Sun
OffRL
88
20
0
26 Jul 2022
Safe Exploration Incurs Nearly No Additional Sample Complexity for
  Reward-free RL
Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-free RL
Ruiquan Huang
J. Yang
Yingbin Liang
OffRL
117
9
0
28 Jun 2022
Provably Efficient Reinforcement Learning in Partially Observable
  Dynamical Systems
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems
Masatoshi Uehara
Ayush Sekhari
Jason D. Lee
Nathan Kallus
Wen Sun
OffRL
101
36
0
24 Jun 2022
Nearly Minimax Optimal Reinforcement Learning with Linear Function
  Approximation
Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation
Pihe Hu
Yu Chen
Longbo Huang
86
35
0
23 Jun 2022
Sample-Efficient Reinforcement Learning of Partially Observable Markov
  Games
Sample-Efficient Reinforcement Learning of Partially Observable Markov Games
Qinghua Liu
Csaba Szepesvári
Chi Jin
114
21
0
02 Jun 2022
Posterior Coreset Construction with Kernelized Stein Discrepancy for
  Model-Based Reinforcement Learning
Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning
Souradip Chakraborty
Amrit Singh Bedi
Alec Koppel
Brian M. Sadler
Furong Huang
Pratap Tokekar
Tianyi Zhou
79
9
0
02 Jun 2022
Stabilizing Q-learning with Linear Architectures for Provably Efficient
  Learning
Stabilizing Q-learning with Linear Architectures for Provably Efficient Learning
Andrea Zanette
Martin J. Wainwright
OOD
125
5
0
01 Jun 2022
Provable General Function Class Representation Learning in Multitask
  Bandits and MDPs
Provable General Function Class Representation Learning in Multitask Bandits and MDPs
Rui Lu
Andrew Zhao
S. Du
Gao Huang
OffRL
104
10
0
31 May 2022
Computationally Efficient Horizon-Free Reinforcement Learning for Linear
  Mixture MDPs
Computationally Efficient Horizon-Free Reinforcement Learning for Linear Mixture MDPs
Dongruo Zhou
Quanquan Gu
122
45
0
23 May 2022
Human-in-the-loop: Provably Efficient Preference-based Reinforcement
  Learning with General Function Approximation
Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation
Xiaoyu Chen
Han Zhong
Zhuoran Yang
Zhaoran Wang
Liwei Wang
192
70
0
23 May 2022
When Is Partially Observable Reinforcement Learning Not Scary?
When Is Partially Observable Reinforcement Learning Not Scary?
Qinghua Liu
Alan Chung
Csaba Szepesvári
Chi Jin
75
98
0
19 Apr 2022
Jump-Start Reinforcement Learning
Jump-Start Reinforcement Learning
Ikechukwu Uchendu
Ted Xiao
Yao Lu
Banghua Zhu
Mengyuan Yan
...
Chuyuan Fu
Cong Ma
Jiantao Jiao
Sergey Levine
Karol Hausman
OffRLOnRL
110
116
0
05 Apr 2022
Near-optimal Offline Reinforcement Learning with Linear Representation:
  Leveraging Variance Information with Pessimism
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism
Ming Yin
Yaqi Duan
Mengdi Wang
Yu Wang
OffRL
123
67
0
11 Mar 2022
A Complete Characterization of Linear Estimators for Offline Policy
  Evaluation
A Complete Characterization of Linear Estimators for Offline Policy Evaluation
Juan C. Perdomo
A. Krishnamurthy
Peter L. Bartlett
Sham Kakade
OffRL
76
3
0
08 Mar 2022
Computational-Statistical Gaps in Reinforcement Learning
Computational-Statistical Gaps in Reinforcement Learning
D. Kane
Sihan Liu
Shachar Lovett
G. Mahajan
57
5
0
11 Feb 2022
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback
Tiancheng Jin
Tal Lancewicki
Haipeng Luo
Yishay Mansour
Aviv A. Rosenberg
131
22
0
31 Jan 2022
Exponential Family Model-Based Reinforcement Learning via Score Matching
Exponential Family Model-Based Reinforcement Learning via Score Matching
Gen Li
Junbo Li
Anmol Kabra
Nathan Srebro
Zhaoran Wang
Zhuoran Yang
90
4
0
28 Dec 2021
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee
Tianhao Wu
Yunchang Yang
Han Zhong
Liwei Wang
S. Du
Jiantao Jiao
112
14
0
21 Dec 2021
Misspecified Gaussian Process Bandit Optimization
Misspecified Gaussian Process Bandit Optimization
Ilija Bogunovic
Andreas Krause
92
45
0
09 Nov 2021
Improved Regret Analysis for Variance-Adaptive Linear Bandits and
  Horizon-Free Linear Mixture MDPs
Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs
Yeoneung Kim
Insoon Yang
Kwang-Sung Jun
100
38
0
05 Nov 2021
Dealing With Misspecification In Fixed-Confidence Linear Top-m
  Identification
Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification
Clémence Réda
Andrea Tirinzoni
Rémy Degenne
64
10
0
02 Nov 2021
Reinforcement Learning in Linear MDPs: Constant Regret and
  Representation Selection
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection
Matteo Papini
Andrea Tirinzoni
Aldo Pacchiano
Marcello Restelli
A. Lazaric
Matteo Pirotta
86
20
0
27 Oct 2021
V-Learning -- A Simple, Efficient, Decentralized Algorithm for
  Multiagent RL
V-Learning -- A Simple, Efficient, Decentralized Algorithm for Multiagent RL
Chi Jin
Qinghua Liu
Yuanhao Wang
Tiancheng Yu
OffRL
90
132
0
27 Oct 2021
Locally Differentially Private Reinforcement Learning for Linear Mixture
  Markov Decision Processes
Locally Differentially Private Reinforcement Learning for Linear Mixture Markov Decision Processes
Chonghua Liao
Jiafan He
Quanquan Gu
77
17
0
19 Oct 2021
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