Evaluation of Deep Reinforcement Learning for Restoration in Optical Networks

A deep reinforcement learning-based agent is presented to perform autonomous lightpath restoration upon a link failure event. The agent is evaluated against other heuristic algorithms under different traffic load and failure duration scenarios. © 2022 The Au-thor(s)