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:

Automated Reinforcement Learning (AutoRL): A Survey and Open Problems
Jack Parker-Holder, Raghu Rajan, Xingyou Song, et al.
Journal of Artificial Intelligence Research (2022) Vol. 74, pp. 517-568
Open Access | Times Cited: 53

Showing 1-25 of 53 citing articles:

Proceedings of the Genetic and Evolutionary Computation Conference
André Biedenkapp, Nguyen Dang, Martin S. Krejca, et al.
(2022)
Open Access | Times Cited: 305
AutoML: A systematic review on automated machine learning with neural architecture search
Imrus Salehin, Md. Shamiul Islam, Pritom Saha, et al.
Journal of Information and Intelligence (2023) Vol. 2, Iss. 1, pp. 52-81
Open Access | Times Cited: 42
An opinions-updating model for large-scale group decision-making driven by autonomous learning
Xiaoting Cheng, Kai Zhang, Tong Wu, et al.
Information Sciences (2024) Vol. 662, pp. 120238-120238
Closed Access | Times Cited: 20
Automated machine learning: past, present and future
Mitra Baratchi, Can Wang, Steffen Limmer, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 5
Open Access | Times Cited: 15
Evolutionary Reinforcement Learning: A Survey
Hui Bai, Ran Cheng, Yaochu Jin
Intelligent Computing (2023) Vol. 2
Open Access | Times Cited: 34
Applications of Machine Learning in Resource Management for RAN-Slicing in 5G and Beyond Networks: A Survey
Yaser Azimi, Saleh Yousefi, Hashem Kalbkhani, et al.
IEEE Access (2022) Vol. 10, pp. 106581-106612
Open Access | Times Cited: 29
General Purpose Artificial Intelligence Systems (GPAIS): Properties, definition, taxonomy, societal implications and responsible governance
Isaac Triguero, Daniel Molina, Javier Poyatos, et al.
Information Fusion (2023) Vol. 103, pp. 102135-102135
Open Access | Times Cited: 21
The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications
Serena Booth, W. Bradley Knox, Julie Shah, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2023) Vol. 37, Iss. 5, pp. 5920-5929
Open Access | Times Cited: 19
Democratizing Artificial Intelligence Imaging Analysis With Automated Machine Learning: Tutorial
Arun James Thirunavukarasu, Kabilan Elangovan, Laura Gutiérrez, et al.
Journal of Medical Internet Research (2023) Vol. 25, pp. e49949-e49949
Open Access | Times Cited: 17
Generative Reward Machine for Reinforcement Learning for Physical Internet Distribution Centre
Saeid Rezaei, Saeid Rezaei
Lecture notes in computer science (2025), pp. 317-332
Closed Access
Combining Evolution and Deep Reinforcement Learning for Policy Search: A Survey
Olivier Sigaud
ACM Transactions on Evolutionary Learning and Optimization (2022) Vol. 3, Iss. 3, pp. 1-20
Open Access | Times Cited: 23
Reinforcement Learning for Autonomous Process Control in Industry 4.0: Advantages and Challenges
Nuria Nievas, Adela Pagès‐Bernaus, Francesc Bonada, et al.
Applied Artificial Intelligence (2024) Vol. 38, Iss. 1
Open Access | Times Cited: 4
Meta-Black-Box optimization for evolutionary algorithms: Review and perspective
Xu Yang, Rui Wang, Kaiwen Li, et al.
Swarm and Evolutionary Computation (2025) Vol. 93, pp. 101838-101838
Closed Access
TARG: Tree of Action-reward Generation With Large Language Model for Cabinet Opening Using Manipulator
Sung-Gil Park, Han-Byeol Kim, Yong Jun Lee, et al.
International Journal of Control Automation and Systems (2025) Vol. 23, Iss. 2, pp. 449-458
Closed Access
Optimizing the hyper-parameters of deep reinforcement learning for building control
Shuhao Li, Shu Su, Xu Lin
Building Simulation (2025)
Closed Access
An empirical study of the naïve REINFORCE algorithm for predictive maintenance
Rajesh Siraskar, Satish Kumar, Shruti Patil, et al.
Deleted Journal (2025) Vol. 7, Iss. 3
Open Access
Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization
Robert Tjarko Lange, Tom Schaul, Yutian Chen, et al.
Proceedings of the Genetic and Evolutionary Computation Conference (2023), pp. 929-937
Open Access | Times Cited: 11
Multi-objective deep reinforcement learning for a water heating system with solar energy and heat recovery
Adrián Riebel, José M. Cardemil, E López
Energy (2024) Vol. 291, pp. 130296-130296
Closed Access | Times Cited: 3
Partial RNA design
Frederic Runge, Jörg K. H. Franke, Daniel Fertmann, et al.
Bioinformatics (2024) Vol. 40, Iss. Supplement_1, pp. i437-i445
Open Access | Times Cited: 3
Sim2real for Autonomous Vehicle Control using Executable Digital Twin
Jean Pierre Allamaa, Panagiotis Patrinos, Herman Van der Auweraer, et al.
IFAC-PapersOnLine (2022) Vol. 55, Iss. 24, pp. 385-391
Open Access | Times Cited: 13
Guided Reinforcement Learning: A Review and Evaluation for Efficient and Effective Real-World Robotics [Survey]
Julian Eßer, Nicolas Bach, Christian Jestel, et al.
IEEE Robotics & Automation Magazine (2022) Vol. 30, Iss. 2, pp. 67-85
Open Access | Times Cited: 12
A Survey on Self-Evolving Autonomous Driving: A Perspective on Data Closed-Loop Technology
Xincheng Li, Zhaoyi Wang, Yanjun Huang, et al.
IEEE Transactions on Intelligent Vehicles (2023) Vol. 8, Iss. 11, pp. 4613-4631
Closed Access | Times Cited: 7
Transfer Reinforcement Learning for Combinatorial Optimization Problems
Gleice Kelly Barbosa Souza, Silva Santos, André Luiz Carvalho Ottoni, et al.
Algorithms (2024) Vol. 17, Iss. 2, pp. 87-87
Open Access | Times Cited: 2
Multi-Objective Reinforcement Learning Based on Decomposition: A Taxonomy and Framework
Florian Felten, El-Ghazali Talbi, Grégoire Danoy
Journal of Artificial Intelligence Research (2024) Vol. 79, pp. 679-723
Open Access | Times Cited: 2
Intersecting reinforcement learning and deep factor methods for optimizing locality and globality in forecasting: A review
João Sousa, Roberto Henriques
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108082-108082
Open Access | Times Cited: 2
Page 1 - Next Page

Scroll to top