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Recent advances in the field of reinforcement learning promise a general approach to optimize networking systems. This paper argues against the recent trend for generalization by introducing a case study where domain-specific modeling enables the application of lightweight and robust learning techniques.
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Daniel S. Berger (2018) studied this question.