Sample-Efficient Autonomous Surface Vehicle Navigation with Enhanced Experience Replay
This paper proposes a sample-efficient reinforcement learning framework for navigation of Autonomous Surface Vehicles (ASVs) in complex, obstacle-dense environments. Learning reliable navigation policies in such settings is challenging due to unsafe early exploration and high sample complexity. To address these issues,...