Guidance Design for Escape Flight Vehicle Using Evolution Strategy Enhanced Deep Reinforcement Learning

Guidance Design for Escape Flight Vehicle Using Evolution Strategy Enhanced Deep Reinforcement Learning

Guidance commands of flight vehicles can be regarded as a series of data sets having fixed time intervals, thus guidance design constitutes a typical sequential decision problem and satisfies the basic conditions for using the deep reinforcement learning (DRL) technique. In this paper, we consider t...

Full description

Bibliographic Details
Main Authors: Xiao Hu, Tianshu Wang, Min Gong, Shaoshi Yang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Deep reinforcement learning
evolution strategy (ES)
guidance design
max-min problem
proximal policy optimization (PPO)
Online Access:https://ieeexplore.ieee.org/document/10485410/

Similar Items

Similar Items