Thomas Avé1, Tom De Schepper2, Kevin Mets3

  • 1IDLab-Department of Computer Science, University of Antwerp-IMEC, Sint-Pietersvliet 7, 2000 Antwerp, Belgium.

PubMed
概括

研究人员开发了一种新的政策蒸方法,以压缩深度强化学习 (DRL) 模型,用于边缘设备上的连续控制任务. 这种技术有效地减少模型大小,同时保持或提高机器人和物联网应用的性能.

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