A Machine Learning Approach to Routing
arXiv:1708.03074
Abstract
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.
References in corpus (5)
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- Trust Region Policy Optimization
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Cited by in corpus (4)
- LIFT: Reinforcement Learning in Computer Systems by Learning From Demonstrations
- Optimizing Redundancy Levels in Master-Worker Compute Clusters for Straggler Mitigation
- Who is Smarter? Intelligence Measure of Learning-based Cognitive Radios
- Wield: Systematic Reinforcement Learning With Progressive Randomization