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Research on the Application of Reinforcement Learning Model in Vocational Education System

Fei Xue*

Department of Information and Art, Nanjing Vocational College of Finance and Economics, Nanjing, 210000, China

* Corresponding Author: Fei Xue. Email: email

Journal on Artificial Intelligence 2023, 5, 131-143. https://doi.org/10.32604/jai.2023.046293

Abstract

Vocational education can effectively improve the vocational skills of employees, improve people’s traditional concept of vocational education, and focus on the training of vocational skills for students by using new educational methods and concepts, so that they can master key vocational skills and develop key abilities. In this paper, three different learning models, Deep Knowledge Tracing (DKT), Dynamic Key-Value Memory Networks (DKVMN) and Double Deep Q-network (DDQN), are used to evaluate the indicators in the vocational education system. On the one hand, the influence of learning degree on the performance of the model is compared, on the other hand, the performance evaluation of three models under the same learning effect is compared, so as to obtain the best learning model applied to the field of skill training. In order to accurately evaluate the learning status of students, the loss function curves under three models are compared. Finally, the error rate of students in vocational skills education tends to be zero, and the learning process of intensive learning effectively improves students’ mastery of skills and key abilities.

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Cite This Article

F. Xue, "Research on the application of reinforcement learning model in vocational education system," Journal on Artificial Intelligence, vol. 5, pp. 131–143, 2023.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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