A Machine Learning Approach to Routing

Asaf Valadarsky, Michael Schapira, Dafna Shahaf, Aviv Tamar

Can ideas and techniques from machine learning be leveraged to automatically generate "good" routing configurations? We investigate the power of data-driven routing protocols. Our results suggest that applying ideas and techniques from deep reinforcement learning to this context yields high performance, motivating further research along these lines.

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