Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Overcoming model bias for robust offline deep reinforcement learning
Phillip Swazinna, Steffen Udluft, Thomas A. Runkler
Engineering Applications of Artificial Intelligence (2021) Vol. 104, pp. 104366-104366
Open Access | Times Cited: 33

Showing 1-25 of 33 citing articles:

Reinforcement learning algorithms: A brief survey
Ashish Kumar Shakya, G. N. Pillai, Sohom Chakrabarty
Expert Systems with Applications (2023) Vol. 231, pp. 120495-120495
Closed Access | Times Cited: 166
A spatial temporal graph neural network model for predicting flashover in arbitrary building floorplans
Wai Cheong Tam, Eugene Yujun Fu, Jiajia Li, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 115, pp. 105258-105258
Closed Access | Times Cited: 26
Reinforcement Learning: A review
Hanae Moussaoui, Nabil El Akkad, Mohamed Benslimane
International Journal of Computing and Digital Systems (2023) Vol. 13, Iss. 1, pp. 1465-1483
Open Access | Times Cited: 12
Bias in Reinforcement Learning: A Review in Healthcare Applications
Benjamin Smith, Anahita Khojandi, Rama K. Vasudevan
ACM Computing Surveys (2023) Vol. 56, Iss. 2, pp. 1-17
Closed Access | Times Cited: 12
An Analysis of Offline Model-Based Learning with Action Noise
Haoya Li, Tanmay Gangwani, Lexing Ying
Journal of Scientific Computing (2025) Vol. 103, Iss. 2
Closed Access
Continuous reinforcement learning via advantage value difference reward shaping: A proximal policy optimization perspective
Jiawei Lin, Xuekai Wei, Weizhi Xian, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 151, pp. 110676-110676
Closed Access
Deep learning feature-based setpoint generation and optimal control for flotation processes
Mingxi Ai, Yongfang Xie, Zhaohui Tang, et al.
Information Sciences (2021) Vol. 578, pp. 644-658
Closed Access | Times Cited: 25
Deep Reinforcement Learning for Personalized Driving Recommendations to Mitigate Aggressiveness and Riskiness: Modeling and Impact Assessment
Eleni G. Mantouka, Eleni I. Vlahogianni
Transportation Research Part C Emerging Technologies (2022) Vol. 142, pp. 103770-103770
Closed Access | Times Cited: 17
Comparing Model-free and Model-based Algorithms for Offline Reinforcement Learning
Phillip Swazinna, Steffen Udluft, Daniel Hein, et al.
IFAC-PapersOnLine (2022) Vol. 55, Iss. 15, pp. 19-26
Open Access | Times Cited: 17
Doubly constrained offline reinforcement learning for learning path recommendation
Yun Yue, Huan Dai, Rui An, et al.
Knowledge-Based Systems (2023) Vol. 284, pp. 111242-111242
Closed Access | Times Cited: 8
Fuzzy-based predictive deep reinforcement learning for robust and constrained optimal control of industrial solar thermal plants
Fitsum Bekele Tilahun
Applied Soft Computing (2024) Vol. 159, pp. 111432-111432
Closed Access | Times Cited: 2
Offline Reinforcement Learning With Behavior Value Regularization
Longyang Huang, Botao Dong, Wei Xie, et al.
IEEE Transactions on Cybernetics (2024) Vol. 54, Iss. 6, pp. 3692-3704
Closed Access | Times Cited: 2
Temporal dilated convolution and nonlinear autoregressive network for predicting solid oxide fuel cell performance
Mohamadali Tofigh, A. Kharazmi, Daniel J. Smith, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 136, pp. 108994-108994
Open Access | Times Cited: 2
A Novel Prediction Model for Debris Flow Mean Velocity Based on Small Sample Data Taking Jiangjia Gully Watershed as an Example
He Kuang, Zhi Yong Ai, Gan Lin Gu
International Journal for Numerical and Analytical Methods in Geomechanics (2024) Vol. 48, Iss. 18, pp. 4399-4409
Closed Access | Times Cited: 2
Safe batch constrained deep reinforcement learning with generative adversarial network
Wenbo Dong, Shaofan Liu, Shiliang Sun
Information Sciences (2023) Vol. 634, pp. 259-270
Closed Access | Times Cited: 5
K-mixup: Data augmentation for offline reinforcement learning using mixup in a Koopman invariant subspace
Junwoo Jang, Jungwoo Han, Jinwhan Kim
Expert Systems with Applications (2023) Vol. 225, pp. 120136-120136
Closed Access | Times Cited: 4
Pessimistic value iteration for multi-task data sharing in Offline Reinforcement Learning
Chenjia Bai, Lingxiao Wang, Jianye Hao, et al.
Artificial Intelligence (2023) Vol. 326, pp. 104048-104048
Open Access | Times Cited: 4
Offline reinforcement learning with representations for actions
Xingzhou Lou, Qiyue Yin, Junge Zhang, et al.
Information Sciences (2022) Vol. 610, pp. 746-758
Closed Access | Times Cited: 3
OCEAN-MBRL: Offline Conservative Exploration for Model-Based Offline Reinforcement Learning
Fan Wu, Rui Zhang, Qi Yi, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 14, pp. 15897-15905
Open Access
Eliciting patient preferences and predicting behaviour using Inverse Reinforcement Learning for telehealth use in outpatient clinics
Aaron J. Snoswell, Centaine L. Snoswell, Nan Ye
Frontiers in Digital Health (2024) Vol. 6
Open Access
Uncertainty-Driven Trajectory Truncation for Data Augmentation in Offline Reinforcement Learning
Junjie Zhang, Jiafei Lyu, Xiaoteng Ma, et al.
Frontiers in artificial intelligence and applications (2023)
Open Access | Times Cited: 1
Model-Based Offline Policy Optimization with Distribution Correcting Regularization
Jian Shen, Mingcheng Chen, Zhicheng Zhang, et al.
Lecture notes in computer science (2021), pp. 174-189
Closed Access | Times Cited: 3
Measuring Data Quality for Dataset Selection in Offline Reinforcement Learning
Phillip Swazinna, Steffen Udluft, Thomas A. Runkler
2021 IEEE Symposium Series on Computational Intelligence (SSCI) (2021), pp. 1-8
Open Access | Times Cited: 3
State Deviation Correction for Offline Reinforcement Learning
Hongchang Zhang, Jianzhun Shao, Yuhang Jiang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2022) Vol. 36, Iss. 8, pp. 9022-9030
Open Access | Times Cited: 2
Learning unsupervised disentangled skill latents to adapt unseen task and morphological modifications
Taewoo Kim, Pamul Yadav, Ho Suk, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 116, pp. 105367-105367
Open Access | Times Cited: 2
Page 1 - Next Page

Scroll to top