An active pursuit strategy for autonomous mobile robots based on deep reinforcement learning-Reference-Cited by-同舟云学术

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An active pursuit strategy for autonomous mobile robots based on deep reinforcement learning

Published:2023-03-24 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Cyborg and Bionic Systems (CBS)
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Author:

Gao Yingnan¹,Cheng Lei²,He Yu³,Wang Duanchu³

Affiliation:

1. Wuhan University of Science and Technology,Control Science and Engineering,Wuhan,China,430081

2. Institute of Robotics and Intelligent Systems, Wuhan University of Science and Technology,Wuhan,China,430081

3. Wuhan University of Science and Technology,School of Information Science and Engineering/School of Artificial Intelligence,Wuhan,China,430081

Funder

Research and Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10115317/10115301/10115383.pdf?arnumber=10115383

Reference15 articles.

1. Asynchronous methods for deep reinforcement learning;mnih;International Conference on Machine Learning,2016

2. Addressing function approximation error in actor-critic methods;fujimoto;International Conference on Machine Learning,2018

3. Mobile Robot Automatic Aiming Method Based on Binocular Vision

4. Soft actor-critic for discrete action settings;christodoulou;arXiv preprint arXiv 1910 07470,2019

5. Soft actor-critic: Offpolicy maximum entropy deep reinforcement learning with a stochastic actor;haarnoja;International Conference on Machine Learning,2018

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