Temporal-IRL learns a reward function for berth scheduling from AIS data, predicting vessel actions, port congestion, and departure times with reported accuracies of 82.64%, 74.06%, and 71.51% respectively.
A methodology to assess vessel berthing and speed optimization policies
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Temporal-IRL: Modeling Port Congestion and Berth Scheduling with Inverse Reinforcement Learning
Temporal-IRL learns a reward function for berth scheduling from AIS data, predicting vessel actions, port congestion, and departure times with reported accuracies of 82.64%, 74.06%, and 71.51% respectively.