An air combat maneuver decision-making approach using coupled reward in deep reinforcement learning

An air combat maneuver decision-making approach using coupled reward in deep reinforcement learning

Abstract In the domain of unmanned air combat, achieving efficient autonomous maneuvering decisions presents challenges. Deep Reinforcement learning(DRL) is one of the approaches to tackle this problem. The final performance of the DRL algorithm is directly affected by the design of the reward funct...

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Bibliographic Details
Main Authors: Jian Yang, Liangpei Wang, Jiale Han, Changdi Chen, Yinlong Yuan, Zhu Liang Yu, Guoli Yang
Format: Article
Language:English
Published: Springer 2025-06-01
Series:Complex & Intelligent Systems
Subjects:
Air combat
Maneuver decision-making
Deep reinforcement learning(DRL)
Coupled reward
Online Access:https://doi.org/10.1007/s40747-025-01992-9
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