ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2306.13601
  4. Cited By
Active Coverage for PAC Reinforcement Learning

Active Coverage for PAC Reinforcement Learning

23 June 2023
Aymen Al Marjani
Andrea Tirinzoni
E. Kaufmann
    OffRL
ArXivPDFHTML

Papers citing "Active Coverage for PAC Reinforcement Learning"

12 / 12 papers shown
Title
The Importance of Non-Markovianity in Maximum State Entropy Exploration
The Importance of Non-Markovianity in Maximum State Entropy Exploration
Mirco Mutti
Ric De Santi
Marcello Restelli
69
31
0
07 Feb 2022
Offline Reinforcement Learning: Fundamental Barriers for Value Function
  Approximation
Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation
Dylan J. Foster
A. Krishnamurthy
D. Simchi-Levi
Yunzong Xu
OffRL
101
62
0
21 Nov 2021
Concave Utility Reinforcement Learning: the Mean-Field Game Viewpoint
Concave Utility Reinforcement Learning: the Mean-Field Game Viewpoint
Matthieu Geist
Julien Pérolat
Mathieu Laurière
Romuald Elie
Sarah Perrin
Olivier Bachem
Rémi Munos
Olivier Pietquin
69
64
0
07 Jun 2021
Leveraging Good Representations in Linear Contextual Bandits
Leveraging Good Representations in Linear Contextual Bandits
Matteo Papini
Andrea Tirinzoni
Marcello Restelli
A. Lazaric
Matteo Pirotta
54
26
0
08 Apr 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
55
64
0
18 Aug 2020
Batch Value-function Approximation with Only Realizability
Batch Value-function Approximation with Only Realizability
Tengyang Xie
Nan Jiang
OffRL
257
120
0
11 Aug 2020
Fast active learning for pure exploration in reinforcement learning
Fast active learning for pure exploration in reinforcement learning
Pierre Ménard
O. D. Domingues
Anders Jonsson
E. Kaufmann
Edouard Leurent
Michal Valko
35
95
0
27 Jul 2020
Adaptive Reward-Free Exploration
Adaptive Reward-Free Exploration
E. Kaufmann
Pierre Ménard
O. D. Domingues
Anders Jonsson
Edouard Leurent
Michal Valko
40
81
0
11 Jun 2020
Active Model Estimation in Markov Decision Processes
Active Model Estimation in Markov Decision Processes
Jean Tarbouriech
S. Shekhar
Matteo Pirotta
Mohammad Ghavamzadeh
A. Lazaric
38
24
0
06 Mar 2020
Non-Asymptotic Pure Exploration by Solving Games
Non-Asymptotic Pure Exploration by Solving Games
Rémy Degenne
Wouter M. Koolen
Pierre Ménard
48
101
0
25 Jun 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
95
274
0
01 Jan 2019
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement
  Learning
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning
Christoph Dann
Tor Lattimore
Emma Brunskill
69
307
0
22 Mar 2017
1