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Provably Efficient Reinforcement Learning with Aggregated States
v1v2 (latest)

Provably Efficient Reinforcement Learning with Aggregated States

13 December 2019
Shi Dong
Benjamin Van Roy
Zhengyuan Zhou
ArXiv (abs)PDFHTML

Papers citing "Provably Efficient Reinforcement Learning with Aggregated States"

21 / 21 papers shown
Demystifying Linear MDPs and Novel Dynamics Aggregation Framework
Demystifying Linear MDPs and Novel Dynamics Aggregation FrameworkInternational Conference on Learning Representations (ICLR), 2024
Joongkyu Lee
Min-hwan Oh
213
5
0
31 Oct 2024
The RL Perceptron: Generalisation Dynamics of Policy Learning in High
  Dimensions
The RL Perceptron: Generalisation Dynamics of Policy Learning in High DimensionsPhysical Review X (PRX), 2023
Nishil Patel
Sebastian Lee
Stefano Sarao Mannelli
Sebastian Goldt
Adrew Saxe
OffRL
431
6
0
17 Jun 2023
Exponential Hardness of Reinforcement Learning with Linear Function
  Approximation
Exponential Hardness of Reinforcement Learning with Linear Function ApproximationAnnual Conference Computational Learning Theory (COLT), 2023
Daniel M. Kane
Sihan Liu
Shachar Lovett
G. Mahajan
Csaba Szepesvári
Gellert Weisz
240
6
0
25 Feb 2023
Tight Guarantees for Interactive Decision Making with the
  Decision-Estimation Coefficient
Tight Guarantees for Interactive Decision Making with the Decision-Estimation CoefficientAnnual Conference Computational Learning Theory (COLT), 2023
Dylan J. Foster
Noah Golowich
Yanjun Han
OffRL
222
29
0
19 Jan 2023
Model-Free Reinforcement Learning with the Decision-Estimation
  Coefficient
Model-Free Reinforcement Learning with the Decision-Estimation CoefficientNeural Information Processing Systems (NeurIPS), 2022
Dylan J. Foster
Noah Golowich
Jian Qian
Alexander Rakhlin
Ayush Sekhari
OffRL
245
12
0
25 Nov 2022
Planning to the Information Horizon of BAMDPs via Epistemic State
  Abstraction
Planning to the Information Horizon of BAMDPs via Epistemic State AbstractionNeural Information Processing Systems (NeurIPS), 2022
Dilip Arumugam
Satinder Singh
193
6
0
30 Oct 2022
A General Framework for Sample-Efficient Function Approximation in
  Reinforcement Learning
A General Framework for Sample-Efficient Function Approximation in Reinforcement LearningInternational Conference on Learning Representations (ICLR), 2022
Zixiang Chen
C. J. Li
An Yuan
Quanquan Gu
Michael I. Jordan
OffRL
220
30
0
30 Sep 2022
Learning to Order for Inventory Systems with Lost Sales and Uncertain
  Supplies
Learning to Order for Inventory Systems with Lost Sales and Uncertain SuppliesManagement Sciences (MS), 2022
Boxiao Chen
Jiashuo Jiang
Jiawei Zhang
Zhengyuan Zhou
226
13
0
10 Jul 2022
On the Complexity of Adversarial Decision Making
On the Complexity of Adversarial Decision MakingNeural Information Processing Systems (NeurIPS), 2022
Dylan J. Foster
Alexander Rakhlin
Ayush Sekhari
Karthik Sridharan
AAML
186
31
0
27 Jun 2022
Deciding What to Model: Value-Equivalent Sampling for Reinforcement
  Learning
Deciding What to Model: Value-Equivalent Sampling for Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2022
Dilip Arumugam
Benjamin Van Roy
OffRL
254
18
0
04 Jun 2022
Finding Safe Zones of policies Markov Decision Processes
Finding Safe Zones of policies Markov Decision ProcessesNeural Information Processing Systems (NeurIPS), 2022
Lee Cohen
Yishay Mansour
Michal Moshkovitz
236
1
0
23 Feb 2022
Computational-Statistical Gaps in Reinforcement Learning
Computational-Statistical Gaps in Reinforcement Learning
D. Kane
Sihan Liu
Shachar Lovett
G. Mahajan
149
5
0
11 Feb 2022
Improved Algorithms for Misspecified Linear Markov Decision Processes
Improved Algorithms for Misspecified Linear Markov Decision Processes
Daniel Vial
Advait Parulekar
Sanjay Shakkottai
R. Srikant
192
7
0
12 Sep 2021
Regret Minimization Experience Replay in Off-Policy Reinforcement
  Learning
Regret Minimization Experience Replay in Off-Policy Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2021
Xu-Hui Liu
Zhenghai Xue
Jing-Cheng Pang
Shengyi Jiang
Feng Xu
Yang Yu
OffRL
176
46
0
15 May 2021
Bilinear Classes: A Structural Framework for Provable Generalization in
  RL
Bilinear Classes: A Structural Framework for Provable Generalization in RLInternational Conference on Machine Learning (ICML), 2021
S. Du
Sham Kakade
Jason D. Lee
Shachar Lovett
G. Mahajan
Wen Sun
Ruosong Wang
OffRL
507
199
0
19 Mar 2021
Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve
  Optimism, Embrace Virtual Curvature
Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual CurvatureNeural Information Processing Systems (NeurIPS), 2021
Kefan Dong
Jiaqi Yang
Tengyu Ma
519
37
0
08 Feb 2021
Randomized Value Functions via Posterior State-Abstraction Sampling
Randomized Value Functions via Posterior State-Abstraction Sampling
Dilip Arumugam
Benjamin Van Roy
OffRL
288
7
0
05 Oct 2020
Approximation Benefits of Policy Gradient Methods with Aggregated States
Approximation Benefits of Policy Gradient Methods with Aggregated States
Daniel Russo
350
7
0
22 Jul 2020
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient
  Learning
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient LearningNeural Information Processing Systems (NeurIPS), 2020
Alekh Agarwal
Mikael Henaff
Sham Kakade
Wen Sun
OffRL
258
119
0
16 Jul 2020
Provably More Efficient Q-Learning in the
  One-Sided-Feedback/Full-Feedback Settings
Provably More Efficient Q-Learning in the One-Sided-Feedback/Full-Feedback Settings
Xiao-Yue Gong
D. Simchi-Levi
92
0
0
30 Jun 2020
Reinforcement Learning with Feedback Graphs
Reinforcement Learning with Feedback Graphs
Christoph Dann
Yishay Mansour
M. Mohri
Ayush Sekhari
Karthik Sridharan
153
9
0
07 May 2020
1