A fast learning approach for autonomous navigation using a deep reinforcement learning method
Deep reinforcement learning-based methods employ an ample amount of computational power that affects the learning process. This paper proposes a novel approach to speed up the training process and improve the performance of autonomous navigation for a tracked robot. The proposed model named �layer...
| Main Authors: | Ejaz, M.M., Tang, T.B., Lu, C.-K. |
|---|---|
| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.29513 / |
| Published: |
John Wiley and Sons Inc
2021
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108902731&doi=10.1049%2fell2.12057&partnerID=40&md5=c8f9304a5a4360dec387fd511a7fafb6 http://eprints.utp.edu.my/29513/ |
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