Distributional and hierarchical reinforcement learning for physical systems with noisy state observations and exogenous perturbations-Reference-Cited by-同舟云学术

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Distributional and hierarchical reinforcement learning for physical systems with noisy state observations and exogenous perturbations

Published:2023-08 Issue: Volume:123 Page:106465
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Park Jehyun^ORCID,Choi Jongeun^ORCID,Nah Sungjae^ORCID,Kim Dohee^ORCID

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference44 articles.

1. A distributional perspective on reinforcement learning;Bellemare,2017

2. Openai gym;Brockman,2016

3. Unsupervised reinforcement learning for transferable manipulation skill discovery;Cho;IEEE Robot. Autom. Lett.,2022

4. Implicit quantile networks for distributional reinforcement learning;Dabney,2018

5. Distributional reinforcement learning with quantile regression;Dabney,2018

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel multi-attention reinforcement learning for the scheduling of unmanned shipment vessels (USV) in automated container terminals;Omega;2024-12

2. How to Design Reinforcement Learning Methods for the Edge: An Integrated Approach toward Intelligent Decision Making;Electronics;2024-03-29

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