A diffusion model is used to augment rewards in deep reinforcement learning for coordinated AIGC workload scheduling and energy management across distributed data centers.
Two-timescale joint optimization of task scheduling and resource scaling in multi-data center system based on multi-agent deep reinforcement learning,
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Joint Energy Management and Coordinated AIGC Workload Scheduling for Distributed Data Centers: A Diffusion-Aided Reward Shaping Approach
A diffusion model is used to augment rewards in deep reinforcement learning for coordinated AIGC workload scheduling and energy management across distributed data centers.