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Deep Echo State Q-Network (DEQN) and Its Application in Dynamic Spectrum
  Sharing for 5G and Beyond

Deep Echo State Q-Network (DEQN) and Its Application in Dynamic Spectrum Sharing for 5G and Beyond

12 October 2020
Hao-Hsuan Chang
Lingjia Liu
Yuhao Yi
ArXivPDFHTML

Papers citing "Deep Echo State Q-Network (DEQN) and Its Application in Dynamic Spectrum Sharing for 5G and Beyond"

7 / 7 papers shown
Title
Distributive Dynamic Spectrum Access through Deep Reinforcement
  Learning: A Reservoir Computing Based Approach
Distributive Dynamic Spectrum Access through Deep Reinforcement Learning: A Reservoir Computing Based Approach
Hao-Hsuan Chang
Hao Song
Yuhao Yi
Jianzhong Zhang
Haibo He
Lingjia Liu
26
164
0
28 Oct 2018
Learning to Play in a Day: Faster Deep Reinforcement Learning by
  Optimality Tightening
Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening
Frank S. He
Yang Liu
Alex Schwing
Jian-wei Peng
58
84
0
05 Nov 2016
Deep Reinforcement Learning with Double Q-learning
Deep Reinforcement Learning with Double Q-learning
H. V. Hasselt
A. Guez
David Silver
OffRL
167
7,639
0
22 Sep 2015
Deep Recurrent Q-Learning for Partially Observable MDPs
Deep Recurrent Q-Learning for Partially Observable MDPs
Matthew J. Hausknecht
Peter Stone
106
1,678
0
23 Jul 2015
End-to-End Training of Deep Visuomotor Policies
End-to-End Training of Deep Visuomotor Policies
Sergey Levine
Chelsea Finn
Trevor Darrell
Pieter Abbeel
BDL
308
3,434
0
02 Apr 2015
Playing Atari with Deep Reinforcement Learning
Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih
Koray Kavukcuoglu
David Silver
Alex Graves
Ioannis Antonoglou
Daan Wierstra
Martin Riedmiller
125
12,227
0
19 Dec 2013
On the difficulty of training Recurrent Neural Networks
On the difficulty of training Recurrent Neural Networks
Razvan Pascanu
Tomas Mikolov
Yoshua Bengio
ODL
190
5,342
0
21 Nov 2012
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