A fast learning approach for autonomous navigation using a deep reinforcement learning method
Abstract 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...
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| Auteurs principaux: | , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Wiley
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/5d00fccac16c4c09b8f53c68bbb338b2 |
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