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References (22)

[1]
Should We Ever Prefer Decision Transformer for Offline Reinforcement Learning?
2025Yumi Omori, Zixuan Dong et al.
[2]
Offline Reinforcement Learning for Mobility Robustness Optimization
2025Pegah Alizadeh, Anastasios Giovanidis et al.
[3]
Offline Reinforcement Learning and Sequence Modeling for Downlink Link Adaptation
2024Samuele Peri, Alessio Russo et al.
[4]
Critic-Guided Decision Transformer for Offline Reinforcement Learning
2023Yuanfu Wang, Chao Yang et al.
[5]
Advancing RAN Slicing with Offline Reinforcement Learning
2023Kun Yang, Shu-ping Yeh et al.
[6]
Offline Reinforcement Learning for Wireless Network Optimization with Mixture Datasets
2023Kun Yang, Cong Shen et al.
[7]
ACT: Empowering Decision Transformer with Dynamic Programming via Advantage Conditioning
2023Chenxiao Gao, Chenyang Wu et al.
[8]
When should we prefer Decision Transformers for Offline Reinforcement Learning?
2023Prajjwal Bhargava, Rohan Chitnis et al.
[9]
Q-learning Decision Transformer: Leveraging Dynamic Programming for Conditional Sequence Modelling in Offline RL
2022Taku Yamagata, Ahmed Khalil et al.
[10]
A Review of Uncertainty for Deep Reinforcement Learning
2022Owen Lockwood, Mei Si
[11]
You Can't Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments
2022Keiran Paster, Sheila A. McIlraith et al.
[12]
mobile-env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks
2022Stefan Schneider, Stefan Werner et al.
[13]
d3rlpy: An Offline Deep Reinforcement Learning Library
2021Takuma Seno, M. Imai
[14]
Offline Reinforcement Learning with Implicit Q-Learning
2021Ilya Kostrikov, Ashvin Nair et al.
[15]
Decision Transformer: Reinforcement Learning via Sequence Modeling
2021Lili Chen, Kevin Lu et al.
[16]
Deep Reinforcement Learning based Wireless Network Optimization: A Comparative Study
2020Kun Yang, Cong Shen et al.
[17]
Conservative Q-Learning for Offline Reinforcement Learning
2020Aviral Kumar, Aurick Zhou et al.
[18]
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
2020S. Levine, Aviral Kumar et al.
[19]
D4RL: Datasets for Deep Data-Driven Reinforcement Learning
2020Justin Fu, Aviral Kumar et al.
[20]
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
2018Tuomas Haarnoja, Aurick Zhou et al.

Showing 20 of 22 references

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"Develop a robust offline RL algorithm toolkit for reliable AI-driven network control in wireless systems."

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