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Provably Efficient Reinforcement Learning in Partially Observable
  Dynamical Systems

Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems

24 June 2022
Masatoshi Uehara
Ayush Sekhari
Jason D. Lee
Nathan Kallus
Wen Sun
    OffRL
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Papers citing "Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems"

5 / 5 papers shown
Title
On the Curses of Future and History in Future-dependent Value Functions
  for Off-policy Evaluation
On the Curses of Future and History in Future-dependent Value Functions for Off-policy Evaluation
Yuheng Zhang
Nan Jiang
OffRL
22
4
0
22 Feb 2024
Provable Benefits of Multi-task RL under Non-Markovian Decision Making
  Processes
Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes
Ruiquan Huang
Yuan-Chia Cheng
Jing Yang
Vincent Tan
Yingbin Liang
11
0
0
20 Oct 2023
Provably Efficient Representation Learning with Tractable Planning in
  Low-Rank POMDP
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP
Jiacheng Guo
Zihao Li
Huazheng Wang
Mengdi Wang
Zhuoran Yang
Xuezhou Zhang
17
5
0
21 Jun 2023
Computationally Efficient PAC RL in POMDPs with Latent Determinism and
  Conditional Embeddings
Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings
Masatoshi Uehara
Ayush Sekhari
Jason D. Lee
Nathan Kallus
Wen Sun
51
6
0
24 Jun 2022
Embed to Control Partially Observed Systems: Representation Learning
  with Provable Sample Efficiency
Embed to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency
Lingxiao Wang
Qi Cai
Zhuoran Yang
Zhaoran Wang
41
17
0
26 May 2022
1