Enhancing BVR Air Combat Agent Development With Attention-Driven Reinforcement Learning

Enhancing BVR Air Combat Agent Development With Attention-Driven Reinforcement Learning

This study explores the use of Reinforcement Learning (RL) to develop autonomous agents for Beyond Visual Range (BVR) air combat, addressing the challenges of dynamic and uncertain adversarial scenarios. We propose a novel approach that introduces a task-based layer, leveraging domain expertise to o...

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Bibliographic Details
Main Authors:	Andre R. Kuroswiski, Annie S. Wu, Angelo Passaro
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Series:	IEEE Access
Subjects:	Adversarial learning artificial intelligence autonomous agents beyond visual range air combat multi-head attention reinforcement learning
Online Access:	https://ieeexplore.ieee.org/document/10966908/
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