Design and performance improvement of virtual reality training simulator based on deep reinforcement learning
Author Names:
Shengnan Gao, Wei Zhao, Xiaoshun Li
Author Affiliation:
College of Intelligent Science and Engineering, Beijing University of Agriculture, Beijing, China
Author Email:
xiaoshun_li@outlook.com
Publication Date:
April 24, 2026
Page numbers:
DOI Number:
https://doi.org/10.1177/14727978251364599
Abstract:
With the rapid development of information technology and artificial intelligence, the application of virtual reality (VR) and reinforcement learning (RL) in education and training has attracted more and more attention. First, this study systematically reviews the latest progress of VR and RL in the field of education and training through literature review. Then, a virtual reality training model based on reinforcement learning is constructed, and the model is verified and evaluated in detail. On the basis of the model training results, the model testing and performance evaluation are further carried out, and the performance of different models is compared. This study not only provides a highly adaptive and personalized training model combining VR and RL, but also verifies its effectiveness in improving education and training results through experiments.
Keywords:
virtual reality, reinforcement learning, model verification, performance evaluation
You need to register before accessing this content.