ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1904.12691
  4. Cited By
DAC: The Double Actor-Critic Architecture for Learning Options

DAC: The Double Actor-Critic Architecture for Learning Options

29 April 2019
Shangtong Zhang
Shimon Whiteson
ArXivPDFHTML

Papers citing "DAC: The Double Actor-Critic Architecture for Learning Options"

13 / 13 papers shown
Title
Optimizing Electric Bus Charging Scheduling with Uncertainties Using Hierarchical Deep Reinforcement Learning
Optimizing Electric Bus Charging Scheduling with Uncertainties Using Hierarchical Deep Reinforcement Learning
Jiaju Qi
Lei Lei
Thorsteinn Jonsson
Dusit Niyato
26
0
0
15 May 2025
Subgoal Discovery Using a Free Energy Paradigm and State Aggregations
Subgoal Discovery Using a Free Energy Paradigm and State Aggregations
Amirhossein Mesbah
Reshad Hosseini
Seyed Pooya Shariatpanahi
M. N. Ahmadabadi
77
0
0
21 Dec 2024
Wasserstein Diversity-Enriched Regularizer for Hierarchical
  Reinforcement Learning
Wasserstein Diversity-Enriched Regularizer for Hierarchical Reinforcement Learning
Haorui Li
Jiaqi Liang
Linjing Li
D. Zeng
11
0
0
02 Aug 2023
Planning Immediate Landmarks of Targets for Model-Free Skill Transfer
  across Agents
Planning Immediate Landmarks of Targets for Model-Free Skill Transfer across Agents
Minghuan Liu
Zhengbang Zhu
Menghui Zhu
Yuzheng Zhuang
Weinan Zhang
Jianye Hao
18
0
0
18 Dec 2022
Dynamic Decision Frequency with Continuous Options
Dynamic Decision Frequency with Continuous Options
Amir-Hossein Karimi
Jun Jin
Jun Luo
A. R. Mahmood
Martin Jägersand
Samuele Tosatto
15
9
0
06 Dec 2022
LEAGUE: Guided Skill Learning and Abstraction for Long-Horizon
  Manipulation
LEAGUE: Guided Skill Learning and Abstraction for Long-Horizon Manipulation
Shuo Cheng
Danfei Xu
54
37
0
23 Oct 2022
On the Robustness of Safe Reinforcement Learning under Observational
  Perturbations
On the Robustness of Safe Reinforcement Learning under Observational Perturbations
Zuxin Liu
Zijian Guo
Zhepeng Cen
Huan Zhang
Jie Tan
Bo-wen Li
Ding Zhao
OOD
OffRL
42
35
0
29 May 2022
Plan Your Target and Learn Your Skills: Transferable State-Only
  Imitation Learning via Decoupled Policy Optimization
Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy Optimization
Minghuan Liu
Zhengbang Zhu
Yuzheng Zhuang
Weinan Zhang
Jianye Hao
Yong Yu
Jun Wang
32
11
0
04 Mar 2022
Flexible Option Learning
Flexible Option Learning
Martin Klissarov
Doina Precup
OffRL
41
26
0
06 Dec 2021
Program Synthesis Guided Reinforcement Learning for Partially Observed
  Environments
Program Synthesis Guided Reinforcement Learning for Partially Observed Environments
Yichen Yang
J. Inala
Osbert Bastani
Yewen Pu
Armando Solar-Lezama
Martin Rinard
42
12
0
22 Feb 2021
Data-efficient Hindsight Off-policy Option Learning
Data-efficient Hindsight Off-policy Option Learning
Markus Wulfmeier
Dushyant Rao
Roland Hafner
Thomas Lampe
A. Abdolmaleki
...
Michael Neunert
Dhruva Tirumala
Noah Y. Siegel
N. Heess
Martin Riedmiller
OffRL
23
47
0
30 Jul 2020
Continuous-Discrete Reinforcement Learning for Hybrid Control in
  Robotics
Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics
Michael Neunert
A. Abdolmaleki
Markus Wulfmeier
Thomas Lampe
Jost Tobias Springenberg
Roland Hafner
Francesco Romano
J. Buchli
N. Heess
Martin Riedmiller
13
91
0
02 Jan 2020
Compositional Transfer in Hierarchical Reinforcement Learning
Compositional Transfer in Hierarchical Reinforcement Learning
Markus Wulfmeier
A. Abdolmaleki
Roland Hafner
Jost Tobias Springenberg
Michael Neunert
Tim Hertweck
Thomas Lampe
Noah Y. Siegel
N. Heess
Martin Riedmiller
19
27
0
26 Jun 2019
1