High-Speed Three-Dimensional Aerial Vehicle Evasion Based on a Multi-Stage Dueling Deep Q-Network

High-Speed Three-Dimensional Aerial Vehicle Evasion Based on a Multi-Stage Dueling Deep Q-Network

This paper proposes a multi-stage dueling deep Q-network (MS-DDQN) algorithm to address the high-speed aerial vehicle evasion problem. High-speed aerial vehicle pursuit and evasion are an ongoing game attracting significant research attention in the field of autonomous aerial vehicle decision making...

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Bibliographic Details
Main Authors: Yefeng Yang, Tao Huang, Xinxin Wang, Chih-Yung Wen, Xianlin Huang
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Aerospace
Subjects:
aerial vehicle evasion
deep reinforcement learning
dueling deep Q-network
multi-stage training
Online Access:https://www.mdpi.com/2226-4310/9/11/673

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