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2003.01629
Cited By
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?
3 March 2020
Keita Ota
Tomoaki Oiki
Devesh K. Jha
T. Mariyama
D. Nikovski
OffRL
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Papers citing
"Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?"
4 / 4 papers shown
Title
Hyperspherical Normalization for Scalable Deep Reinforcement Learning
Hojoon Lee
Youngdo Lee
Takuma Seno
Donghu Kim
Peter Stone
Jaegul Choo
63
1
0
24 Feb 2025
Cross-Domain Policy Adaptation by Capturing Representation Mismatch
Jiafei Lyu
Chenjia Bai
Jingwen Yang
Zongqing Lu
Xiu Li
30
8
0
24 May 2024
Bridging State and History Representations: Understanding Self-Predictive RL
Tianwei Ni
Benjamin Eysenbach
Erfan Seyedsalehi
Michel Ma
Clement Gehring
Aditya Mahajan
Pierre-Luc Bacon
AI4TS
AI4CE
22
20
0
17 Jan 2024
A Survey on Transformers in Reinforcement Learning
Wenzhe Li
Hao Luo
Zichuan Lin
Chongjie Zhang
Zongqing Lu
Deheng Ye
OffRL
MU
AI4CE
37
55
0
08 Jan 2023
1