A Q-learning approach to the continuous control problem of robot inverted pendulum balancing-Reference-Cited by-同舟云学术

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A Q-learning approach to the continuous control problem of robot inverted pendulum balancing

Published:2024-03 Issue: Volume:21 Page:200313
ISSN:2667-3053
Container-title:Intelligent Systems with Applications
language:en
Short-container-title:Intelligent Systems with Applications

Author:

Safeea Mohammad^ORCID,Neto Pedro^ORCID

Funder

Fundação para a Ciência e a Tecnologia

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,Computer Vision and Pattern Recognition,Signal Processing,Computer Science (miscellaneous)

Reference31 articles.

1. Learning robust manipulation skills with guided policy search via generative motor reflexes;Ennen,2019

2. Q-learning in continuous state and action spaces;Gaskett,1999

3. Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates;Gu,2017

4. Continuous deep q-learning with model-based acceleration;Gu,2016

5. Q-learning algorithms: A comprehensive classification and applications;Jang;IEEE Access,2019

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. Study of Q-learning and deep Q-network learning control for a rotary inverted pendulum system;Discover Applied Sciences;2024-02-02

2. Dual Mode Control of an Inverted Pendulum: Design, Analysis and Experimental Evaluation;Advances in Science, Technology and Engineering Systems Journal;2023-12

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