An Experience Aggregative Reinforcement Learning With Multi-Attribute Decision-Making for Obstacle Avoidance of Wheeled Mobile Robot

A variety of reinforcement learning (RL) methods are developed to achieve the motion control for the robotic systems, which has been a hot issue. However, the performance of the conventional RL methods often encounters a bottleneck, because the robots have difficulty in choosing an appropriate actio...

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Bibliographic Details
Main Authors: Chunyang Hu, Bin Ning, Meng Xu, Qiong Gu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9112198/

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