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On Lower Bounds for Regret in Reinforcement Learning

On Lower Bounds for Regret in Reinforcement Learning

9 August 2016
Ian Osband
Benjamin Van Roy
ArXivPDFHTML

Papers citing "On Lower Bounds for Regret in Reinforcement Learning"

35 / 35 papers shown
Title
Reinforcement Learning from Multi-level and Episodic Human Feedback
Reinforcement Learning from Multi-level and Episodic Human Feedback
Muhammad Qasim Elahi
Somtochukwu Oguchienti
Maheed H. Ahmed
Mahsa Ghasemi
OffRL
50
0
0
20 Apr 2025
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
Jasmine Bayrooti
Carl Henrik Ek
Amanda Prorok
42
0
0
07 Oct 2024
Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation
Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation
Taehyun Cho
Seung Han
Kyungjae Lee
Seokhun Ju
Dohyeong Kim
Jungwoo Lee
64
0
0
31 Jul 2024
Cascading Reinforcement Learning
Cascading Reinforcement Learning
Yihan Du
R. Srikant
Wei Chen
19
0
0
17 Jan 2024
Learning in POMDPs is Sample-Efficient with Hindsight Observability
Learning in POMDPs is Sample-Efficient with Hindsight Observability
Jonathan Lee
Alekh Agarwal
Christoph Dann
Tong Zhang
34
19
0
31 Jan 2023
Multi-armed Bandit Learning on a Graph
Multi-armed Bandit Learning on a Graph
Tianpeng Zhang
Kasper Johansson
Na Li
25
6
0
20 Sep 2022
Making Linear MDPs Practical via Contrastive Representation Learning
Making Linear MDPs Practical via Contrastive Representation Learning
Tianjun Zhang
Tongzheng Ren
Mengjiao Yang
Joseph E. Gonzalez
Dale Schuurmans
Bo Dai
25
44
0
14 Jul 2022
Provably Efficient Kernelized Q-Learning
Provably Efficient Kernelized Q-Learning
Shuang Liu
H. Su
MLT
25
4
0
21 Apr 2022
Branching Reinforcement Learning
Branching Reinforcement Learning
Yihan Du
Wei Chen
27
0
0
16 Feb 2022
Continual Learning In Environments With Polynomial Mixing Times
Continual Learning In Environments With Polynomial Mixing Times
Matthew D Riemer
Sharath Chandra Raparthy
Ignacio Cases
G. Subbaraj
M. P. Touzel
Irina Rish
CLL
41
8
0
13 Dec 2021
A Free Lunch from the Noise: Provable and Practical Exploration for
  Representation Learning
A Free Lunch from the Noise: Provable and Practical Exploration for Representation Learning
Tongzheng Ren
Tianjun Zhang
Csaba Szepesvári
Bo Dai
24
19
0
22 Nov 2021
Settling the Horizon-Dependence of Sample Complexity in Reinforcement
  Learning
Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning
Yuanzhi Li
Ruosong Wang
Lin F. Yang
25
20
0
01 Nov 2021
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free
  Reinforcement Learning
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning
Gen Li
Laixi Shi
Yuxin Chen
Yuejie Chi
OffRL
45
50
0
09 Oct 2021
Reward Poisoning in Reinforcement Learning: Attacks Against Unknown
  Learners in Unknown Environments
Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments
Amin Rakhsha
Xuezhou Zhang
Xiaojin Zhu
Adish Singla
AAML
OffRL
41
37
0
16 Feb 2021
Learning Adversarial Markov Decision Processes with Delayed Feedback
Learning Adversarial Markov Decision Processes with Delayed Feedback
Tal Lancewicki
Aviv A. Rosenberg
Yishay Mansour
32
32
0
29 Dec 2020
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
Qinghua Liu
Tiancheng Yu
Yu Bai
Chi Jin
32
121
0
04 Oct 2020
Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs
Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs
Jiafan He
Dongruo Zhou
Quanquan Gu
6
37
0
01 Oct 2020
Adaptive Discretization for Model-Based Reinforcement Learning
Adaptive Discretization for Model-Based Reinforcement Learning
Sean R. Sinclair
Tianyu Wang
Gauri Jain
Siddhartha Banerjee
Chao Yu
OffRL
11
21
0
01 Jul 2020
Provably Efficient Reinforcement Learning for Discounted MDPs with
  Feature Mapping
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping
Dongruo Zhou
Jiafan He
Quanquan Gu
30
133
0
23 Jun 2020
Near-Optimal Reinforcement Learning with Self-Play
Near-Optimal Reinforcement Learning with Self-Play
Yunru Bai
Chi Jin
Tiancheng Yu
19
129
0
22 Jun 2020
$Q$-learning with Logarithmic Regret
QQQ-learning with Logarithmic Regret
Kunhe Yang
Lin F. Yang
S. Du
43
59
0
16 Jun 2020
Reinforcement Learning with General Value Function Approximation:
  Provably Efficient Approach via Bounded Eluder Dimension
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension
Ruosong Wang
Ruslan Salakhutdinov
Lin F. Yang
23
55
0
21 May 2020
Learning Zero-Sum Simultaneous-Move Markov Games Using Function
  Approximation and Correlated Equilibrium
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium
Qiaomin Xie
Yudong Chen
Zhaoran Wang
Zhuoran Yang
39
124
0
17 Feb 2020
Provable Self-Play Algorithms for Competitive Reinforcement Learning
Provable Self-Play Algorithms for Competitive Reinforcement Learning
Yu Bai
Chi Jin
SSL
14
148
0
10 Feb 2020
Making Sense of Reinforcement Learning and Probabilistic Inference
Making Sense of Reinforcement Learning and Probabilistic Inference
Brendan O'Donoghue
Ian Osband
Catalin Ionescu
OffRL
22
47
0
03 Jan 2020
Influence-Based Multi-Agent Exploration
Influence-Based Multi-Agent Exploration
Tonghan Wang
Jianhao Wang
Yi Wu
Chongjie Zhang
18
137
0
12 Oct 2019
Provably Efficient Reinforcement Learning with Linear Function
  Approximation
Provably Efficient Reinforcement Learning with Linear Function Approximation
Chi Jin
Zhuoran Yang
Zhaoran Wang
Michael I. Jordan
21
539
0
11 Jul 2019
Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy
  Policies
Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies
Yonathan Efroni
Nadav Merlis
Mohammad Ghavamzadeh
Shie Mannor
OffRL
22
67
0
27 May 2019
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning
  without Domain Knowledge using Value Function Bounds
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds
Andrea Zanette
Emma Brunskill
OffRL
21
272
0
01 Jan 2019
Exploration in Structured Reinforcement Learning
Exploration in Structured Reinforcement Learning
Jungseul Ok
Alexandre Proutière
Damianos Tranos
17
62
0
03 Jun 2018
Efficient Bias-Span-Constrained Exploration-Exploitation in
  Reinforcement Learning
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning
Ronan Fruit
Matteo Pirotta
A. Lazaric
R. Ortner
21
115
0
12 Feb 2018
Deep Exploration via Randomized Value Functions
Deep Exploration via Randomized Value Functions
Ian Osband
Benjamin Van Roy
Daniel Russo
Zheng Wen
33
301
0
22 Mar 2017
Minimax Regret Bounds for Reinforcement Learning
Minimax Regret Bounds for Reinforcement Learning
M. G. Azar
Ian Osband
Rémi Munos
16
759
0
16 Mar 2017
Stochastic Primal-Dual Methods and Sample Complexity of Reinforcement
  Learning
Stochastic Primal-Dual Methods and Sample Complexity of Reinforcement Learning
Yichen Chen
Mengdi Wang
24
64
0
08 Dec 2016
Why is Posterior Sampling Better than Optimism for Reinforcement
  Learning?
Why is Posterior Sampling Better than Optimism for Reinforcement Learning?
Ian Osband
Benjamin Van Roy
BDL
17
255
0
01 Jul 2016
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