Variational Information Bottleneck Regularized Deep Reinforcement Learning for Efficient Robotic Skill Adaptation

Deep Reinforcement Learning (DRL) algorithms have been widely studied for sequential decision-making problems, and substantial progress has been achieved, especially in autonomous robotic skill learning. However, it is always difficult to deploy DRL methods in practical safety-critical robot systems...

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Bibliografiska uppgifter

Huvudupphov:	Guofei Xiang, Songyi Dian, Shaofeng Du, Zhonghui Lv
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	MDPI AG 2023-01-01
Serie:	Sensors
Ämnen:	reinforcement learning (RL) meta-learning information bottleneck deep neural networks skill transfer robotics
Länkar:	https://www.mdpi.com/1424-8220/23/2/762
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