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PBCS : Efficient Exploration and Exploitation Using a Synergy between
  Reinforcement Learning and Motion Planning

PBCS : Efficient Exploration and Exploitation Using a Synergy between Reinforcement Learning and Motion Planning

24 April 2020
Guillaume Matheron
Nicolas Perrin
Olivier Sigaud
ArXivPDFHTML

Papers citing "PBCS : Efficient Exploration and Exploitation Using a Synergy between Reinforcement Learning and Motion Planning"

7 / 7 papers shown
Title
Leveraging Sequentiality in Reinforcement Learning from a Single
  Demonstration
Leveraging Sequentiality in Reinforcement Learning from a Single Demonstration
Alexandre Chenu
Olivier Serris
Olivier Sigaud
Nicolas Perrin-Gilbert
26
4
0
09 Nov 2022
Cell-Free Latent Go-Explore
Cell-Free Latent Go-Explore
Quentin Gallouedec
Emmanuel Dellandrea
19
1
0
31 Aug 2022
Play with Emotion: Affect-Driven Reinforcement Learning
Play with Emotion: Affect-Driven Reinforcement Learning
M. Barthet
Ahmed Khalifa
Antonios Liapis
Georgios N. Yannakakis
CVBM
27
7
0
26 Aug 2022
Generative Personas That Behave and Experience Like Humans
Generative Personas That Behave and Experience Like Humans
M. Barthet
Ahmed Khalifa
Antonios Liapis
Georgios N. Yannakakis
21
20
0
26 Aug 2022
Exploration in Deep Reinforcement Learning: A Survey
Exploration in Deep Reinforcement Learning: A Survey
Pawel Ladosz
Lilian Weng
Minwoo Kim
H. Oh
OffRL
26
324
0
02 May 2022
Divide & Conquer Imitation Learning
Divide & Conquer Imitation Learning
Alexandre Chenu
Nicolas Perrin-Gilbert
Olivier Sigaud
16
5
0
15 Apr 2022
Go-Blend behavior and affect
Go-Blend behavior and affect
M. Barthet
Antonios Liapis
Georgios N. Yannakakis
28
7
0
24 Sep 2021
1