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IEEE/ICACT20230243 Slide.08        [Big Slide]       [YouTube]	Oral Presentation
	The main contributions of this paper are as follows: For model, we introduce Dynamic voltage and frequency scaling and energy harvest technology into the task offloading framework in D2D-assisted MEC network to minimize the average task delay under strict energy constraints. For algorithm: we use a multi-agent reinforcement learning algorithm based on MAPPO to deal with the multi-dimensional discrete action spaces and complex cooperative relationships between devices. And we have proved the effectiveness and superiority of our algorithm through sufficient experiments.

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