Enhancing Robotic Manipulation: Harnessing the Power of Multi-Task Reinforcement Learning and Single Life Reinforcement Learning in Meta-World

At present, robots typically require extensive training to successfully accomplish a single task. However, to truly enhance their usefulness in real-world scenarios, robots should possess the capability to perform multiple tasks effectively. To address this need, various multi-task reinforcement lea...

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Veröffentlicht in:	arXiv.org 2023-10
Hauptverfasser:	Nehme, Ghadi, Sabane, Ishan, Deo, Tejas Y
Format:	Artikel
Sprache:	eng
Schlagworte:	Ablation Algorithms Machine learning Optimization Research projects Robot arms Robotics Robots
Online-Zugang:	Volltext
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