Dual-Agent Hierarchical Reinforcement Learning for Typhoon-Avoidance Route Planning of Ships Under Dynamic Wind–Wave–Current Fields
Ship weather routing in regional seas under severe seasonal weather systems, such as typhoons, poses a critical operational challenge for maritime safety and efficiency. Traditional single-agent reinforcement learning (RL) methods frequently suffer from training instabilities and erratic trajectory adjustments when exp...