Path planning for a maritime surface ship based on Deep Reinforcement Learning and weather forecast
Résumé
Artificial Intelligence (AI) algorithms as decision support assist operators to choose appropriate decisions in naval missions. This article offers a decision support model to predict the path of a Maritime Surface Ship (MSS) in a dynamic environment by using Deep Reinforcement Learning (DRL). In this way, we suggest taking into account weather forecast and simplified static and mobile obstacles.
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