An Applied Study of Improved Deep Q-Networks for Marine Path Planning

This study tackles challenges in maritime path planning, a key concern in industries like shipping and offshore oil, by introducing an enhanced Deep Q-Network (DQN) that incorporates Navigational Priority (NP) and Priority Experience Replay (PER). Utilizing a Gym-based simulation, the enhanced DQN outperforms traditional and baseline methods in both path optimization and computational efficiency, validating the use of Priority Experience Replay and suggesting new avenues for addressing complex problems.