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Fast active learning for pure exploration in reinforcement learning

Fast active learning for pure exploration in reinforcement learning

27 July 2020
Pierre Ménard
O. D. Domingues
Anders Jonsson
E. Kaufmann
Edouard Leurent
Michal Valko
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Papers citing "Fast active learning for pure exploration in reinforcement learning"

27 / 27 papers shown
Title
Cascading Reinforcement Learning
Cascading Reinforcement Learning
Yihan Du
R. Srikant
Wei Chen
19
0
0
17 Jan 2024
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
51
1
0
16 Oct 2023
When is Agnostic Reinforcement Learning Statistically Tractable?
When is Agnostic Reinforcement Learning Statistically Tractable?
Zeyu Jia
Gene Li
Alexander Rakhlin
Ayush Sekhari
Nathan Srebro
OffRL
32
5
0
09 Oct 2023
Policy Finetuning in Reinforcement Learning via Design of Experiments
  using Offline Data
Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data
Ruiqi Zhang
Andrea Zanette
OffRL
OnRL
42
7
0
10 Jul 2023
Active Sensing with Predictive Coding and Uncertainty Minimization
Active Sensing with Predictive Coding and Uncertainty Minimization
A. Sharafeldin
N. Imam
Hannah Choi
22
3
0
02 Jul 2023
Towards Theoretical Understanding of Inverse Reinforcement Learning
Towards Theoretical Understanding of Inverse Reinforcement Learning
Alberto Maria Metelli
Filippo Lazzati
Marcello Restelli
29
13
0
25 Apr 2023
Improved Sample Complexity for Reward-free Reinforcement Learning under
  Low-rank MDPs
Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs
Yuan Cheng
Ruiquan Huang
J. Yang
Yitao Liang
OffRL
41
8
0
20 Mar 2023
Active learning for data streams: a survey
Active learning for data streams: a survey
Davide Cacciarelli
M. Kulahci
30
40
0
17 Feb 2023
Concentration Bounds for Discrete Distribution Estimation in KL
  Divergence
Concentration Bounds for Discrete Distribution Estimation in KL Divergence
C. Canonne
Ziteng Sun
A. Suresh
79
4
0
14 Feb 2023
Layered State Discovery for Incremental Autonomous Exploration
Layered State Discovery for Incremental Autonomous Exploration
Liyu Chen
Andrea Tirinzoni
A. Lazaric
Matteo Pirotta
34
0
0
07 Feb 2023
Cell-Free Latent Go-Explore
Cell-Free Latent Go-Explore
Quentin Gallouedec
Emmanuel Dellandrea
19
1
0
31 Aug 2022
On the Statistical Efficiency of Reward-Free Exploration in Non-Linear
  RL
On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL
Jinglin Chen
Aditya Modi
A. Krishnamurthy
Nan Jiang
Alekh Agarwal
38
25
0
21 Jun 2022
BYOL-Explore: Exploration by Bootstrapped Prediction
BYOL-Explore: Exploration by Bootstrapped Prediction
Z. Guo
S. Thakoor
Miruna Pislar
Bernardo Avila-Pires
Florent Altché
...
Yunhao Tang
Michal Valko
Rémi Munos
M. G. Azar
Bilal Piot
22
68
0
16 Jun 2022
Provably Efficient Risk-Sensitive Reinforcement Learning: Iterated CVaR
  and Worst Path
Provably Efficient Risk-Sensitive Reinforcement Learning: Iterated CVaR and Worst Path
Yihan Du
Siwei Wang
Longbo Huang
OOD
24
13
0
06 Jun 2022
Exploration in Deep Reinforcement Learning: A Survey
Exploration in Deep Reinforcement Learning: A Survey
Pawel Ladosz
Lilian Weng
Minwoo Kim
H. Oh
OffRL
26
324
0
02 May 2022
Branching Reinforcement Learning
Branching Reinforcement Learning
Yihan Du
Wei Chen
27
0
0
16 Feb 2022
Provably Efficient Causal Model-Based Reinforcement Learning for
  Systematic Generalization
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization
Mirco Mutti
Ric De Santi
Emanuele Rossi
J. Calderón
Michael M. Bronstein
Marcello Restelli
30
14
0
14 Feb 2022
Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost
Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost
Dan Qiao
Ming Yin
Ming Min
Yu-Xiang Wang
43
28
0
13 Feb 2022
Gap-Dependent Unsupervised Exploration for Reinforcement Learning
Gap-Dependent Unsupervised Exploration for Reinforcement Learning
Jingfeng Wu
Vladimir Braverman
Lin F. Yang
33
12
0
11 Aug 2021
Navigating to the Best Policy in Markov Decision Processes
Navigating to the Best Policy in Markov Decision Processes
Aymen Al Marjani
Aurélien Garivier
Alexandre Proutiere
35
21
0
05 Jun 2021
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in
  Time-Homogeneous, Reward-Free and Task-Agnostic Settings
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings
Ming Yin
Yu-Xiang Wang
OffRL
32
19
0
13 May 2021
UCB Momentum Q-learning: Correcting the bias without forgetting
UCB Momentum Q-learning: Correcting the bias without forgetting
Pierre Menard
O. D. Domingues
Xuedong Shang
Michal Valko
79
41
0
01 Mar 2021
Improved Corruption Robust Algorithms for Episodic Reinforcement
  Learning
Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
Yifang Chen
S. Du
Kevin G. Jamieson
24
22
0
13 Feb 2021
Task-Optimal Exploration in Linear Dynamical Systems
Task-Optimal Exploration in Linear Dynamical Systems
Andrew Wagenmaker
Max Simchowitz
Kevin G. Jamieson
22
18
0
10 Feb 2021
Provably Efficient Reward-Agnostic Navigation with Linear Value
  Iteration
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration
Andrea Zanette
A. Lazaric
Mykel J. Kochenderfer
Emma Brunskill
30
64
0
18 Aug 2020
A Provably Efficient Sample Collection Strategy for Reinforcement
  Learning
A Provably Efficient Sample Collection Strategy for Reinforcement Learning
Jean Tarbouriech
Matteo Pirotta
Michal Valko
A. Lazaric
OffRL
25
16
0
13 Jul 2020
Reward-Free Exploration for Reinforcement Learning
Reward-Free Exploration for Reinforcement Learning
Chi Jin
A. Krishnamurthy
Max Simchowitz
Tiancheng Yu
OffRL
112
194
0
07 Feb 2020
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