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Air Dominance Through Machine Learning
Air Dominance Through Machine Learning
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U.S. air superiority is being challenged by competitors. The authors of this report demonstrate a prototype of a proof-of-concept artificial intelligence system to help develop and evaluate new concepts of operations for the air domain. The initial findings highlight both the potential of reinforcement learning to tackle complex, collaborative air mission planning problems, and some significant challenges facing this approach.
  • Leidėjas:
  • ISBN-10: 1977405150
  • ISBN-13: 9781977405159
  • Formatas: 21.6 x 27.9 x 0.4 cm, minkšti viršeliai
  • Kalba: Anglų

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U.S. air superiority is being challenged by competitors. The authors of this report demonstrate a prototype of a proof-of-concept artificial intelligence system to help develop and evaluate new concepts of operations for the air domain. The initial findings highlight both the potential of reinforcement learning to tackle complex, collaborative air mission planning problems, and some significant challenges facing this approach.

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  • Autorius: Li Ang Zhang
  • Leidėjas:
  • ISBN-10: 1977405150
  • ISBN-13: 9781977405159
  • Formatas: 21.6 x 27.9 x 0.4 cm, minkšti viršeliai
  • Kalba: Anglų

U.S. air superiority is being challenged by competitors. The authors of this report demonstrate a prototype of a proof-of-concept artificial intelligence system to help develop and evaluate new concepts of operations for the air domain. The initial findings highlight both the potential of reinforcement learning to tackle complex, collaborative air mission planning problems, and some significant challenges facing this approach.

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