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Physics-Constrained Backdoor Attacks on Power System Fault Localization
The advances in deep learning (DL) techniques have the potential to deliver transformative technological breakthroughs to numerous complex tasks in modern power systems that suffer from increasing uncertainty and nonlinearity.
MACC: Cross-Layer Multi-Agent Congestion Control with Deep Reinforcement Learning
In this paper, we explore the performance of multi-agent reinforcement learning-based cross-layer congestion control algorithms and present cooperation performance of two agents, known as MACC (Multi-agent Congestion Control).
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