Explainable Artificial Intelligence Techniques for the Analysis of Reinforcement Learning in Non-Linear Flight Regimes

Reinforcement Learning is being increasingly applied to flight control tasks, with the objective of developing truly autonomous flying vehicles able to traverse highly variable environments and adapt to unknown situations or possible failures. However, the development of these increasingly complex models and algorithms further reduces our...

Reinforcement Learning for Flight Control: Hybrid Offline-Online Learning for Robust and Adaptive Fault-Tolerance

Recent advancements in fault-tolerant flight control have involved model-free offline and online Reinforcement Learning algorithms in order to provide robust and adaptive control to autonomous systems. Inspired by recent work on Incremental Dual Heuristic Programming (IDHP) and Soft Actor-Critic (SAC), this research proposes a hybrid SAC-IDHP...