Self-starting fiber mode-locked laser assisted with DDQN algorithm

Here, we investigate the performance of Double-Deep Q-learning (DDQL) algorithm for designing self-starting fiber laser. Fiber mode-locked laser based on nonlinear polarization effect was chosen as an experimental platform. We show that the proposed algorithm is capable to learn non-trivial hysteresis dynamics inside the laser in order to achieve stable soliton generation.