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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9864208/ https://www.ncbi.nlm.nih.gov/pubmed/36679561 http://dx.doi.org/10.3390/s23020762 |