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Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical
  Comparison

Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison

9 March 2020
Tengyang Xie
Nan Jiang
ArXivPDFHTML

Papers citing "Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison"

2 / 2 papers shown
Title
On the Theory of Policy Gradient Methods: Optimality, Approximation, and
  Distribution Shift
On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift
Alekh Agarwal
Sham Kakade
Jason D. Lee
G. Mahajan
46
320
0
01 Aug 2019
On the Use of Non-Stationary Policies for Stationary Infinite-Horizon
  Markov Decision Processes
On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes
B. Scherrer
Boris Lesner
OffRL
52
52
0
29 Nov 2012
1