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Tackling Uncertainty in Reinforcement Learning: A Dual Variational Inference Approach for Task and State Estimation Cover

Tackling Uncertainty in Reinforcement Learning: A Dual Variational Inference Approach for Task and State Estimation

International Journal of Advanced Network, Monitoring and Controls
Volume 10 (2025): Issue 3 (September 2025)
By: Zhidong Yang,  Haoyu Liu,  Zongxin Yao and  Hongge Yao  
Open Access
|Sep 2025

Authors

Zhidong Yang

yang.6390@buckeyemail.osu.edu

Ohio State University, Computer Science & Engineering, Columbus, OH, USA

Haoyu Liu

1121227983@qq.com

Xi’an Technological University Computer Science and Engineering Xi’an, China

Zongxin Yao

yaozongxin@xatu.edu.cn

Xi’an Technological University, Computer Science and Engineering, Xi’an, China

Hongge Yao

yaohongge@xatu.edu.cn

Xi’an Technological University Computer Science and Engineering Xi’an, China
DOI: https://doi.org/10.2478/ijanmc-2025-0030 | Journal eISSN: 2470-8038
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Language: English
Page range: 101 - 115
Published on: Sep 30, 2025
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Reinforcement Learning,
Meta Learning,
Fuzzy Uncertainty Information,
Gray Uncertainty Information,
Variational Inference
Related subjects:
Computer sciences,
Computer sciences, other

© 2025 Zhidong Yang, Haoyu Liu, Zongxin Yao, Hongge Yao, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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