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Spatially Randomized Designs Can Enhance Policy Evaluation

Spatially Randomized Designs Can Enhance Policy Evaluation

18 March 2024
Ying Yang
Chengchun Shi
Fang Yao
Shouyang Wang
Hongtu Zhu
    OffRL
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Papers citing "Spatially Randomized Designs Can Enhance Policy Evaluation"

3 / 3 papers shown
Title
Policy Evaluation for Temporal and/or Spatial Dependent Experiments
Policy Evaluation for Temporal and/or Spatial Dependent Experiments
S. Luo
Ying Yang
Chengchun Shi
Fang Yao
Jieping Ye
Hongtu Zhu
43
5
0
22 Feb 2022
A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation
  in Two-sided Markets
A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets
C. Shi
Runzhe Wan
Ge Song
S. Luo
R. Song
Hongtu Zhu
OffRL
35
6
0
21 Feb 2022
Double Reinforcement Learning for Efficient Off-Policy Evaluation in
  Markov Decision Processes
Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes
Nathan Kallus
Masatoshi Uehara
OffRL
38
181
0
22 Aug 2019
1