Flash-Attention-Enhanced Multi-Agent Deep Deterministic Policy Gradient for Mobile Edge Computing in Digital Twin-Powered Internet of Things

Offloading decisions and resource allocation problems in mobile edge computing (MEC) emerge as key challenges as they directly impact system performance and user experience in dynamic and resource-constrained Internet of Things (IoT) environments. This paper constructs a comprehensive and layered di...

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Bibliographic Details
Main Authors:	Yuzhe Gao, Xiaoming Yuan, Songyu Wang, Lixin Chen, Zheng Zhang, Tianran Wang
Format:	Article
Language:	English
Published:	MDPI AG 2025-07-01
Series:	Mathematics
Subjects:	Internet of Things mobile edge computing digital twin multi-agent reinforcement learning attention mechanism flash attention
Online Access:	https://www.mdpi.com/2227-7390/13/13/2164
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Flash-Attention-Enhanced Multi-Agent Deep Deterministic Policy Gradient for Mobile Edge Computing in Digital Twin-Powered Internet of Things

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