#lstm.

Machine Learning for Thermal-Soaring Optimisation: a Survey of Approaches, Architectures and Open Problems

A survey of deep learning and reinforcement learning for autonomous thermal soaring — LSTM/GRU/TCN/Transformer architectures, POMDP and PPO/TD3 formulations, Kalman + ML hybrid filtering, and a concrete five-stage plan for an on-board AI co-pilot for paragliders.