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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Bibliographic Details
Main Authors: Muhammad Mudassir Ejaz, Tong Boon Tang, Cheng‐Kai Lu
Format: article
Language:EN
Published: Wiley 2021
Subjects:
Online Access:https://doaj.org/article/5d00fccac16c4c09b8f53c68bbb338b2
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