Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
1302.2553
Cited By
v1
v2 (latest)
Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning
11 February 2013
Odalric-Ambrym Maillard
P. Nguyen
R. Ortner
D. Ryabko
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning"
11 / 11 papers shown
Title
An Analysis of Model-Based Reinforcement Learning From Abstracted Observations
Rolf A. N. Starre
Marco Loog
E. Congeduti
F. Oliehoek
OffRL
59
1
0
30 Aug 2022
Regret Balancing for Bandit and RL Model Selection
Yasin Abbasi-Yadkori
Aldo Pacchiano
My Phan
87
26
0
09 Jun 2020
Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes
Ronan Fruit
Matteo Pirotta
A. Lazaric
84
62
0
06 Jul 2018
A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity
Pablo Hernandez-Leal
Michael Kaisers
T. Baarslag
Enrique Munoz de Cote
88
275
0
28 Jul 2017
Extreme State Aggregation Beyond MDPs
Marcus Hutter
170
23
0
12 Jul 2014
Selecting Near-Optimal Approximate State Representations in Reinforcement Learning
R. Ortner
Odalric-Ambrym Maillard
D. Ryabko
238
27
0
12 May 2014
The Sample-Complexity of General Reinforcement Learning
Tor Lattimore
Marcus Hutter
P. Sunehag
VLM
113
67
0
22 Aug 2013
Regret Bounds for Reinforcement Learning with Policy Advice
M. G. Azar
A. Lazaric
Emma Brunskill
127
36
0
05 May 2013
Unsupervised model-free representation learning
D. Ryabko
CML
AI4TS
35
2
0
17 Apr 2013
Online Regret Bounds for Undiscounted Continuous Reinforcement Learning
R. Ortner
D. Ryabko
OffRL
120
85
0
11 Feb 2013
Regret Bounds for Restless Markov Bandits
R. Ortner
D. Ryabko
P. Auer
Rémi Munos
125
117
0
12 Sep 2012
1