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Optimal Regret Bounds for Selecting the State Representation in
  Reinforcement Learning

Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning

11 February 2013
Odalric-Ambrym Maillard
P. Nguyen
R. Ortner
D. Ryabko
ArXivPDFHTML

Papers citing "Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning"

6 / 6 papers shown
Title
Selecting the State-Representation in Reinforcement Learning
Selecting the State-Representation in Reinforcement Learning
Odalric-Ambrym Maillard
Rémi Munos
D. Ryabko
54
40
0
11 Feb 2013
Online Regret Bounds for Undiscounted Continuous Reinforcement Learning
Online Regret Bounds for Undiscounted Continuous Reinforcement Learning
R. Ortner
D. Ryabko
OffRL
69
85
0
11 Feb 2013
Predictive State Representations: A New Theory for Modeling Dynamical
  Systems
Predictive State Representations: A New Theory for Modeling Dynamical Systems
Satinder Singh
Michael R. James
Matthew R. Rudary
AI4TS
AI4CE
66
288
0
11 Jul 2012
REGAL: A Regularization based Algorithm for Reinforcement Learning in
  Weakly Communicating MDPs
REGAL: A Regularization based Algorithm for Reinforcement Learning in Weakly Communicating MDPs
Peter L. Bartlett
Ambuj Tewari
71
280
0
09 May 2012
Feature Reinforcement Learning: Part I: Unstructured MDPs
Feature Reinforcement Learning: Part I: Unstructured MDPs
Marcus Hutter
72
67
0
09 Jun 2009
On the Possibility of Learning in Reactive Environments with Arbitrary
  Dependence
On the Possibility of Learning in Reactive Environments with Arbitrary Dependence
D. Ryabko
Marcus Hutter
57
24
0
31 Oct 2008
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