• Corpus ID: 244729393

MAMRL: Exploiting Multi-agent Meta Reinforcement Learning in WAN Traffic Engineering

  title={MAMRL: Exploiting Multi-agent Meta Reinforcement Learning in WAN Traffic Engineering},
  author={Shan Sun and M. Kiran and Wei Ren},
Traffic optimization challenges, such as load balancing, flow scheduling, and improving packet delivery time, are difficult online decision-making problems in wide area networks (WAN). Complex heuristics are needed for instance to find optimal paths that improve packet delivery time and minimize interruptions which may be caused by link failures or congestion. The recent success of reinforcement learning (RL) algorithms can provide useful solutions to build better robust systems that learn from… 

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