Amir Kooshan Fattah

METTA: Memory-Enhanced Test-Time Adaptation for Meta-Reinforcement Learning

Meta-reinforcement learning aims to train agents that adapt quickly to unseen tasks from limited interaction, but this requires representing task evidence over long interaction histories. Classical recurrent agents compress experience into hidden states, while transformer-based agents retrieve from past trajectories at...