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TempoRL: Learning When to Act

TempoRL: Learning When to Act

9 June 2021
André Biedenkapp
Raghunandan Rajan
Frank Hutter
Marius Lindauer
    OffRL
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Papers citing "TempoRL: Learning When to Act"

15 / 15 papers shown
Title
Overcoming Slow Decision Frequencies in Continuous Control: Model-Based Sequence Reinforcement Learning for Model-Free Control
Overcoming Slow Decision Frequencies in Continuous Control: Model-Based Sequence Reinforcement Learning for Model-Free Control
Devdhar Patel
H. Siegelmann
OffRL
37
0
0
11 Oct 2024
When to Sense and Control? A Time-adaptive Approach for Continuous-Time
  RL
When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL
Lenart Treven
Bhavya Sukhija
Yarden As
Florian Dorfler
Andreas Krause
39
0
0
03 Jun 2024
Learning Uncertainty-Aware Temporally-Extended Actions
Learning Uncertainty-Aware Temporally-Extended Actions
Joongkyu Lee
Seung Joon Park
Yunhao Tang
Min-hwan Oh
19
2
0
08 Feb 2024
Open the Black Box: Step-based Policy Updates for Temporally-Correlated
  Episodic Reinforcement Learning
Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning
Ge Li
Hongyi Zhou
Dominik Roth
Serge Thilges
Fabian Otto
Rudolf Lioutikov
Gerhard Neumann
OffRL
27
7
0
21 Jan 2024
Temporal Transfer Learning for Traffic Optimization with Coarse-grained
  Advisory Autonomy
Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomy
Jung-Hoon Cho
Sirui Li
Jeongyun Kim
Cathy Wu
19
3
0
27 Nov 2023
Actor-Critic with variable time discretization via sustained actions
Actor-Critic with variable time discretization via sustained actions
Jakub Lyskawa
Pawel Wawrzyñski
OffRL
15
0
0
08 Aug 2023
Model-based Offline Reinforcement Learning with Count-based Conservatism
Model-based Offline Reinforcement Learning with Count-based Conservatism
Byeongchang Kim
Min Hwan Oh
OffRL
17
12
0
21 Jul 2023
Temporally Layered Architecture for Adaptive, Distributed and Continuous
  Control
Temporally Layered Architecture for Adaptive, Distributed and Continuous Control
Devdhar Patel
Joshua Russell
Frances Walsh
T. Rahman
Terrance Sejnowski
H. Siegelmann
AI4CE
43
1
0
25 Dec 2022
Simultaneously Updating All Persistence Values in Reinforcement Learning
Simultaneously Updating All Persistence Values in Reinforcement Learning
Luca Sabbioni
Luca Al Daire
L. Bisi
Alberto Maria Metelli
Marcello Restelli
29
2
0
21 Nov 2022
Temporally Extended Successor Representations
Temporally Extended Successor Representations
Matthew J. Sargent
Peter J Bentley
Caswell Barry
W. D. Cothi
26
1
0
25 Sep 2022
Automated Dynamic Algorithm Configuration
Automated Dynamic Algorithm Configuration
Steven Adriaensen
André Biedenkapp
Gresa Shala
Noor H. Awad
Theresa Eimer
Marius Lindauer
Frank Hutter
32
36
0
27 May 2022
Generative Planning for Temporally Coordinated Exploration in
  Reinforcement Learning
Generative Planning for Temporally Coordinated Exploration in Reinforcement Learning
Haichao Zhang
Wei-ping Xu
Haonan Yu
38
10
0
24 Jan 2022
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems
Jack Parker-Holder
Raghunandan Rajan
Xingyou Song
André Biedenkapp
Yingjie Miao
...
Vu-Linh Nguyen
Roberto Calandra
Aleksandra Faust
Frank Hutter
Marius Lindauer
AI4CE
33
100
0
11 Jan 2022
TAAC: Temporally Abstract Actor-Critic for Continuous Control
TAAC: Temporally Abstract Actor-Critic for Continuous Control
Haonan Yu
Wei-ping Xu
Haichao Zhang
OffRL
15
21
0
13 Apr 2021
MDP Playground: An Analysis and Debug Testbed for Reinforcement Learning
MDP Playground: An Analysis and Debug Testbed for Reinforcement Learning
Raghunandan Rajan
Jessica Lizeth Borja Diaz
Suresh Guttikonda
Fabio Ferreira
André Biedenkapp
Jan Ole von Hartz
Frank Hutter
33
3
0
17 Sep 2019
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