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Learning in POMDPs is Sample-Efficient with Hindsight Observability
Jonathan N. Lee
, Alekh Agarwal
, Christoph Dann
,
Tong Zhang
Research output
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peer-review
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Computer Science
Cardinality
100%
Data Center
100%
Decision Making
100%
Function Approximation
100%
Learning Process
100%
Markov Decision Process
100%
Partial Observability
100%
Robotics
100%
Keyphrases
Cardinality
25%
Data Center Scheduling
25%
Decision-making Problem
25%
Function Approximation
25%
Hardness Results
25%
Latent State
50%
Learning Process
25%
Markov Decision Process
25%
Partial Observability
25%
Partially Observable Markov Decision Process
100%
Real-world Problems
25%
Robotics
25%
Sample Efficiency
100%
Mathematics
Approximation Function
25%
Cardinality
25%
Data Center
25%
Markov Decision Process
25%
Partially Observable Markov Decision Process
100%