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The Effect of Multi-step Methods on Overestimation in Deep Reinforcement
  Learning

The Effect of Multi-step Methods on Overestimation in Deep Reinforcement Learning

23 June 2020
Lingheng Meng
R. Gorbet
Dana Kulić
    OffRL
ArXivPDFHTML

Papers citing "The Effect of Multi-step Methods on Overestimation in Deep Reinforcement Learning"

4 / 4 papers shown
Title
Neuroplastic Expansion in Deep Reinforcement Learning
Neuroplastic Expansion in Deep Reinforcement Learning
Jiashun Liu
J. Obando-Ceron
Aaron C. Courville
L. Pan
42
3
0
10 Oct 2024
ETGL-DDPG: A Deep Deterministic Policy Gradient Algorithm for Sparse Reward Continuous Control
ETGL-DDPG: A Deep Deterministic Policy Gradient Algorithm for Sparse Reward Continuous Control
Ehsan Futuhi
Shayan Karimi
Chao Gao
Martin Müller
38
1
0
07 Oct 2024
Long N-step Surrogate Stage Reward to Reduce Variances of Deep
  Reinforcement Learning in Complex Problems
Long N-step Surrogate Stage Reward to Reduce Variances of Deep Reinforcement Learning in Complex Problems
Junmin Zhong
Ruofan Wu
J. Si
LRM
13
0
0
10 Oct 2022
Deep Generalized Schrödinger Bridge
Deep Generalized Schrödinger Bridge
Guan-Horng Liu
T. Chen
Oswin So
Evangelos A. Theodorou
OT
AI4CE
13
35
0
20 Sep 2022
1