Research Progress of Opponent Modeling Based on Deep Reinforcement Learning

Authors

Haotian Xu, College of Systems Engineering, National University of Denfense Technology, Changsha 410073, China;Follow
Long Qin, College of Systems Engineering, National University of Denfense Technology, Changsha 410073, China;
Junjie Zeng, College of Systems Engineering, National University of Denfense Technology, Changsha 410073, China;
Yue Hu, College of Systems Engineering, National University of Denfense Technology, Changsha 410073, China;
Qi Zhang, College of Systems Engineering, National University of Denfense Technology, Changsha 410073, China;Follow

Abstract

Abstract: Deep reinforcement learning is an agent modeling method with both deep learning feature extraction ability and reinforcement learning sequence decision-making ability, which can make up for the depleted non-stationary adaptation, complex feature selection and insufficient state-space representation ability of traditional opponent modeling. The deep reinforcement learning-based opponent modeling methods are divided into two categories, explicit modeling and implicit modeling, and the corresponding theories, models, algorithms and applicable scenarios are sorted out according to the categories. The applications of deep reinforcement learning-based opponent modeling techniques on different fields are introduced. The key problems and future development are summarized to provide a comprehensive research review for the deep reinforcement learning-based opponent modeling methods.

Recommended Citation

Xu, Haotian; Qin, Long; Zeng, Junjie; Hu, Yue; and Zhang, Qi (2023) "Research Progress of Opponent Modeling Based on Deep Reinforcement Learning," Journal of System Simulation: Vol. 35: Iss. 4, Article 1.
DOI: 10.16182/j.issn1004731x.joss.22-0555
Available at: https://dc-china-simulation.researchcommons.org/journal/vol35/iss4/1

First Page

671

Revised Date

2022-06-26

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.22-0555

Last Page

694

CLC

TP391.9

Recommended Citation

Haotian Xu, Long Qin, Junjie Zeng, Yue Hu, Qi Zhang. Research Progress of Opponent Modeling Based on Deep Reinforcement Learning[J]. Journal of System Simulation, 2023, 35(4): 671-694.

Corresponding Author

Qi Zhang,zhangqiy123@nudt.edu.cn

DOI

10.16182/j.issn1004731x.joss.22-0555