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OpenAlex Citation Counts

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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:

What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study
Marcin Andrychowicz, Anton Raichuk, Piotr Stańczyk, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 98

Showing 1-25 of 98 citing articles:

Autonomous Unmanned Aerial Vehicle navigation using Reinforcement Learning: A systematic review
Fadi AlMahamid, Katarina Grolinger
Engineering Applications of Artificial Intelligence (2022) Vol. 115, pp. 105321-105321
Open Access | Times Cited: 71
Privacy Preserving Load Control of Residential Microgrid via Deep Reinforcement Learning
Zhaoming Qin, Di Liu, Haochen Hua, et al.
IEEE Transactions on Smart Grid (2021) Vol. 12, Iss. 5, pp. 4079-4089
Closed Access | Times Cited: 78
Applications of Generative AI in Healthcare: algorithmic, ethical, legal and societal considerations
Onyekachukwu R. Okonji, Kamol Yunusov, Bonnie Gordon
(2024)
Open Access | Times Cited: 8
What Matters in Learning from Offline Human Demonstrations for Robot Manipulation
Ajay Mandlekar, Danfei Xu, Josiah Wong, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 52
Phasic Policy Gradient
Karl Cobbe, Jacob Hilton, Oleg Klimov, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 49
Rethinking the Implementation Tricks and Monotonicity Constraint in Cooperative Multi-Agent Reinforcement Learning
Jian Hu, Siyang Jiang, Seth Austin Harding, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 28
Minimizing Energy Cost in PV Battery Storage Systems Using Reinforcement Learning
Florus Härtel, Thilo Bocklisch
IEEE Access (2023) Vol. 11, pp. 39855-39865
Open Access | Times Cited: 11
Deep reinforcement learning navigation via decision transformer in autonomous driving
Lun Ge, Xiaoguang Zhou, Yongqiang Li, et al.
Frontiers in Neurorobotics (2024) Vol. 18
Open Access | Times Cited: 4
Correcting Unsteady Low Order Discontinuous Galerkin Simulations
Anna Kiener, Philipp Bekemeyer
AIAA SCITECH 2022 Forum (2025)
Closed Access
Missile Avoidance Using Reinforcement Learning
Vlad Gavra, A. J. C. Cook, Stefan Neumeier, et al.
AIAA SCITECH 2022 Forum (2025)
Closed Access
Duck Curve Aware Dynamic Pricing and Battery Scheduling Strategy Using Reinforcement Learning
Daichi Watari, Ittetsu Taniguchi, Takao Onoye
IEEE Transactions on Smart Grid (2023) Vol. 15, Iss. 1, pp. 457-471
Open Access | Times Cited: 10
Deep Reinforcement Learning for Cognitive Radar Spectrum Sharing: A Continuous Control Approach
Shane Flandermeyer, Rylee G. Mattingly, Justin G. Metcalf
IEEE Transactions on Radar Systems (2024) Vol. 2, pp. 125-137
Closed Access | Times Cited: 3
Decentralized control and local information for robust and adaptive decentralized Deep Reinforcement Learning
Malte Schilling, Andrew Melnik, Frank W. Ohl, et al.
Neural Networks (2021) Vol. 144, pp. 699-725
Open Access | Times Cited: 23
Multi-Agent Reinforcement Learning Controller to Maximize Energy Efficiency for Multi-Generator Industrial Wave Energy Converter
Soumyendu Sarkar, Vineet Gundecha, Alexander Shmakov, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2022) Vol. 36, Iss. 11, pp. 12135-12144
Open Access | Times Cited: 15
What Matters for Adversarial Imitation Learning?
Manu Orsini, Anton Raichuk, Léonard Hussenot, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 18
Reinforcement Learning Controller Design for Discrete-Time-Constrained Nonlinear Systems With Weight Initialization Method
Jiahui Xu, Jingcheng Wang, Yanjiu Zhong, et al.
IEEE Transactions on Systems Man and Cybernetics Systems (2024) Vol. 54, Iss. 4, pp. 2368-2378
Closed Access | Times Cited: 2
Learning to Locomote: Understanding How Environment Design Matters for Deep Reinforcement Learning
Daniele Reda, Tianxin Tao, Michiel van de Panne
(2020)
Open Access | Times Cited: 17
Benchmarking Potential Based Rewards for Learning Humanoid Locomotion
Se Hwan Jeon, Steve Heim, Charles Khazoom, et al.
(2023)
Open Access | Times Cited: 6
Frustratingly Easy Regularization on Representation Can Boost Deep Reinforcement Learning
Qiang He, Huangyuan Su, Jieyu Zhang, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023)
Open Access | Times Cited: 6
Equivariant Graph-Representation-Based Actor–Critic Reinforcement Learning for Nanoparticle Design
Jonas Elsborg, Arghya Bhowmik
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 12, pp. 3731-3741
Closed Access | Times Cited: 5
Comparative Evaluation of Multi-Agent Deep Reinforcement Learning Algorithms.
Georgios Papoudakis, Filippos Christianos, Lukas Schäfer, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 13
Observation Space Matters: Benchmark and Optimization Algorithm
Joanne Taery Kim, Sehoon Ha
(2021), pp. 1527-1534
Open Access | Times Cited: 11
A Comparison of Reinforcement Learning and Deep Trajectory Based Stochastic Control Agents for Stepwise Mean-Variance Hedging
Ali Fathi, Bernhard Hientzsch
SSRN Electronic Journal (2023)
Open Access | Times Cited: 4
Multi-Agent Deep Reinforcement Learning for Coordinated Multipoint in Mobile Networks
Stefan Schneider, Holger Karl, Ramin Khalili, et al.
IEEE Transactions on Network and Service Management (2023) Vol. 21, Iss. 1, pp. 908-924
Closed Access | Times Cited: 4
What matters in reinforcement learning for tractography
Antoine Théberge, Christian Desrosiers, Arnaud Boré, et al.
Medical Image Analysis (2024) Vol. 93, pp. 103085-103085
Open Access | Times Cited: 1
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