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A Deep Reinforcement Learning Approach for Adaptive Traffic Routing in Next-gen Networks
We adopt the Deep Q-Learning technique to train the DGCNN model in the DRL framework without the need for a labeled training dataset, enabling the framework to quickly adapt to traffic dynamics.
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