Reinforcement-Learning-Router
PublicThis project implements a reinforcement learning-based packet scheduler for a simulated router handling multiple traffic classes (video, voice, and best-effort). The goal is to meet delay-based QoS constraints while minimizing latency, using model-free RL techniques such as Q-Learning.
deep-q-networkgymgym-environmentmachine-learningnetworkingpacket-schedulerppo-agentpytorchreinforcement-learning-agentreinforcement-learning-environments
Creat：2025-05-14T15:21:43
Update：2025-07-29T09:58:45
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