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...
Guardado en:
Autores principales: | Muhammad Mudassir Ejaz, Tong Boon Tang, Cheng‐Kai Lu |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Wiley
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/5d00fccac16c4c09b8f53c68bbb338b2 |
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