A Comprehensive Review of Reinforcement Learning in Intelligent Allocation and Optimization of Educational Resources

Zhonglin Zhao

doi:10.70393/6a6374616d.323436

OPEN ACCESS |Research Article ||16 December 2024

A Comprehensive Review of Reinforcement Learning in Intelligent Allocation and Optimization of Educational Resources

Zhonglin Zhao

Meicheng East, LLC

zhonglintj@outlook.com

Meicheng East, LLC, USA.

* Corresponding Author¹: Zhonglin Zhao, E-Mail: zhonglintj@outlook.com

Publication

Accepted Unknow ; Published 2024 December 16

Journal of Economic Theory and Business Management, 2024, 1(6), 3006-4953.

Abstract

Educational resource imbalances pose considerable barriers to accomplishing equitable opportunities to learn worldwide. Traditional approaches to resource allocation frequently fail to adapt to the ever-changing and intricate needs of educational systems, exacerbating disparities. This paper explores applying reinforcement learning (RL) in optimizing how resources in education are distributed and used, offering a promising solution to these hurdles. The analysis delves into fundamental RL concepts and algorithms, like deep reinforcement learning and multi-agent reinforcement learning, and investigates their applications in customized learning, scheduling resources, and promoting fairness. It highlights major difficulties such as information quality, scalability, fairness, and transparency, along with possibilities for innovation through blended methodologies and instant decision making. By combining existing research and distinguishing critical gaps, this study provides practical insights for advancing RL applications in education, paving the way for more inclusive and effective systems for managing resources.

Keywords

Reinforcement Learning , Educational Resource Optimization , Equity in Education , Multi-Agent Systems , Personalized Learning , Resource Scheduling , Hybrid AI Approaches , Educational Data Quality .

Metadata

DOI:

10.70393/6a6374616d.323436

ARK:

ark:/40704/JETBM.v1n6a03

Pages: 15-24

References: 20

Disciplines: Artificial Intelligence and Intelligence

Subjects: Machine Learning

Cite This Article

APA Style

Zhao, Z. (2024). A comprehensive review of reinforcement learning in intelligent allocation and optimization of educational resources. Journal of Economic Theory and Business Management, 1(6), 15-24. https://doi.org/10.70393/6a6374616d.323436

Acknowledgments

The authors thank the editor and anonymous reviewers for their helpful comments and valuable suggestions.

FUNDING

Not applicable.

INSTITUTIONAL REVIEW BOARD STATEMENT

Not applicable.

DATA AVAILABILITY STATEMENT

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

INFORMED CONSENT STATEMENT

Not applicable.

CONFLICT OF INTEREST

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

AUTHOR CONTRIBUTIONS

Not applicable.

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