Graph-based network optimization model to minimize delay and congestion in networks. Unlike conventional algorithms, our model overcomes limitations by considering a broader range of network parameters. Formulated a Deep Reinforcement Learning (DRL) approach with a custom environment, reward function, and agent capable of learning optimal policy.
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View Code? Open in Web Editor NEWGraph-based network optimization model to minimize delay and congestion in networks. Unlike conventional algorithms, our model overcomes limitations by considering a broader range of network parameters. Formulated a Deep Reinforcement Learning (DRL) approach with a custom environment, reward function, and agent capable of learning optimal policy.