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Decision support system based on Deep Reinforcement Learning for war ships facing asymmetric threats

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Fabien Chaillan
  • Fonction : Auteur
  • PersonId : 839832
Aldo Napoli

Résumé

Intensive information analysis related to a ship and its environment is required in order to make the appropriate decisions during naval missions. However, human capabilities are no longer sufficient to reliably and rapidly process the massive amount of heterogeneous data collected by a huge lot of different sensors. That is the reason why Artificial Intelligence (AI) algorithms as decision support could help operators to choose the appropriate decisions during naval missions. This article offers a decision support model able to assist operators in choosing the most appropriate weapon when facing asymmetric threats in a dynamic environment by Deep Reinforcement Learning (DRL).
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Dates et versions

hal-03696075 , version 1 (15-06-2022)

Identifiants

  • HAL Id : hal-03696075 , version 1

Citer

Eva Artusi, Fabien Chaillan, Aldo Napoli. Decision support system based on Deep Reinforcement Learning for war ships facing asymmetric threats. Undersea Defence Technology (UDT) 2022, Jun 2022, Rotterdam, Netherlands. ⟨hal-03696075⟩
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