Empirical comparison finds Mamba with PPO superior to LSTM/GRU and SAC variants for meta-RL tuning of ICCBF class-K functions in cooperative and adversarial spacecraft RPO simulations.
An Autonomous, End-to-End, Convex- Based Framework for Close-Range Rendezvous Trajectory Design and Guidance with Hardware Testbed Validation,
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Memory-Efficient Meta-Reinforcement Learning for Adaptive Safety-Critical Control in Adversarial Spacecraft Proximity Operations
Empirical comparison finds Mamba with PPO superior to LSTM/GRU and SAC variants for meta-RL tuning of ICCBF class-K functions in cooperative and adversarial spacecraft RPO simulations.