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Exploiting the Sign of the Advantage Function to Learn Deterministic
  Policies in Continuous Domains
v1v2 (latest)

Exploiting the Sign of the Advantage Function to Learn Deterministic Policies in Continuous Domains

International Joint Conference on Artificial Intelligence (IJCAI), 2019
10 June 2019
Matthieu Zimmer
Paul Weng
ArXiv (abs)PDFHTML

Papers citing "Exploiting the Sign of the Advantage Function to Learn Deterministic Policies in Continuous Domains"

3 / 3 papers shown
Time-Varying Constraint-Aware Reinforcement Learning for Energy Storage
  Control
Time-Varying Constraint-Aware Reinforcement Learning for Energy Storage Control
Jaeik Jeong
Tai-Yeon Ku
Wan-Ki Park
139
1
0
17 May 2024
Coordinate Ascent for Off-Policy RL with Global Convergence Guarantees
Coordinate Ascent for Off-Policy RL with Global Convergence GuaranteesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Hsin-En Su
Yen-Ju Chen
Ping-Chun Hsieh
Xi Liu
OffRL
282
1
0
10 Dec 2022
The problem with DDPG: understanding failures in deterministic
  environments with sparse rewards
The problem with DDPG: understanding failures in deterministic environments with sparse rewardsInternational Conference on Artificial Neural Networks (ICANN), 2019
Guillaume Matheron
Nicolas Perrin
Olivier Sigaud
165
73
0
26 Nov 2019
1
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