Tactical intent-driven autonomous air combat behavior generation method

Tactical intent-driven autonomous air combat behavior generation method

Abstract With the rapid development and deep application of artificial intelligence, modern air combat is incrementally evolving towards intelligent combat. Although deep reinforcement learning algorithms have contributed to dramatic advances in in air combat, they still face challenges such as poor...

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Bibliographic Details
Main Authors: Xingyu Wang, Zhen Yang, Shiyuan Chai, Jichuan Huang, Yupeng He, Deyun Zhou
Format: Article
Language:English
Published: Springer 2024-12-01
Series:Complex & Intelligent Systems
Subjects:
Tactical intent
Behavioural strategies
Reward design
Deep reinforcement learning
Online Access:https://doi.org/10.1007/s40747-024-01685-9
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https://doi.org/10.1007/s40747-024-01685-9

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