Open Access Helper

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:

A practical guide to multi-objective reinforcement learning and planning
Conor F. Hayes, Roxana Rădulescu, Eugenio Bargiacchi, et al.
Autonomous Agents and Multi-Agent Systems (2022) Vol. 36, Iss. 1
Open Access | Times Cited: 161

Showing 1-25 of 161 citing articles:

Explainable AI Over the Internet of Things (IoT): Overview, State-of-the-Art and Future Directions
Senthil Kumar Jagatheesaperumal, Quoc‐Viet Pham, Rukhsana Ruby, et al.
IEEE Open Journal of the Communications Society (2022) Vol. 3, pp. 2106-2136
Open Access | Times Cited: 69
A State‐of‐the‐Art Review of Optimal Reservoir Control for Managing Conflicting Demands in a Changing World
Matteo Giuliani, Jonathan Lamontagne, Patrick M. Reed, et al.
Water Resources Research (2021) Vol. 57, Iss. 12
Open Access | Times Cited: 89
Pembentukan Karakter Religius Siswa Melalui Pembelajaran Pendidikan Agama Islam di Sekolah Menengah Kejuruan
Mar’atul Azizah, Safinatul Jariah, Andika Aprilianto
Deleted Journal (2023) Vol. 1, Iss. 1, pp. 29-45
Open Access | Times Cited: 22
Explainable reinforcement learning for broad-XAI: a conceptual framework and survey
Richard Dazeley, Peter Vamplew, Francisco Cruz
Neural Computing and Applications (2023) Vol. 35, Iss. 23, pp. 16893-16916
Open Access | Times Cited: 21
A Review of Deep Reinforcement Learning Approaches for Smart Manufacturing in Industry 4.0 and 5.0 Framework
Alejandro J. del Real, Doru Stefan Andreiana, Álvaro Ojeda Roldán, et al.
Applied Sciences (2022) Vol. 12, Iss. 23, pp. 12377-12377
Open Access | Times Cited: 36
Goals, usefulness and abstraction in value-based choice
Benedetto De Martino, Aurelio Cortese
Trends in Cognitive Sciences (2022) Vol. 27, Iss. 1, pp. 65-80
Open Access | Times Cited: 32
Deep multi-objective reinforcement learning for utility-based infrastructural maintenance optimization
Jesse van Remmerden, Maurice Kenter, Diederik M. Roijers, et al.
Neural Computing and Applications (2025)
Open Access
HephaestusForge: Optimal microservice deployment across the Compute Continuum via Reinforcement Learning
José Santos, Mattia Zaccarini, Filippo Poltronieri, et al.
Future Generation Computer Systems (2025), pp. 107680-107680
Closed Access
A R2 Based Multi-objective Reinforcement Learning Algorithm
Stephen D. Miller, Carlos Hernández
Lecture notes in computer science (2025), pp. 285-289
Closed Access
Testing the Limits of the World's Largest Control Task
Eshaan Agrawal, Christian Schroeder de Witt
(2025), pp. 171-205
Closed Access
Minimising the relative regret of future forest landscape compositions: The role of close-to-nature stand types
Thomas Knoke, Peter Biber, Tobias Schula, et al.
Forest Policy and Economics (2025) Vol. 171, pp. 103410-103410
Open Access
From fair solutions to compromise solutions in multi-objective deep reinforcement learning
Junqi Qian, Umer Siddique, Guanbao Yu, et al.
Neural Computing and Applications (2025)
Closed Access
HPRS: hierarchical potential-based reward shaping from task specifications
Luigi Berducci, Edgar A. Aguilar, Dejan Ničković, et al.
Frontiers in Robotics and AI (2025) Vol. 11
Open Access
Investigating the performance of multi-objective reinforcement learning techniques in the context of IoT with harvesting energy
Bakhta Haouari, Rania Mzid, Olfa Mosbahi
The Journal of Supercomputing (2025) Vol. 81, Iss. 4
Closed Access
Explaining Task Delegation Through Argumentation Debates with Votes
Jeferson José Baqueta, César Augusto Tacla
Lecture notes in computer science (2025), pp. 372-383
Closed Access
Context-Aware Machine Learning for Smart Manufacturing
Vagan Terziyan, Oleksandra Vitko
Procedia Computer Science (2025) Vol. 253, pp. 25-36
Open Access
Extending Power Electronic Converter Lifetime in Marine Hydrokinetic Turbines with Reinforcement Learning
Samuel J. Barton, Ted Brekken, Yue Cao
Applied Sciences (2025) Vol. 15, Iss. 5, pp. 2512-2512
Open Access
Multi-objective Sequential Decision Making for Holistic Supply Chain Optimization
Rifny Rachman, Josh Tingey, Richard Allmendinger, et al.
Lecture notes in computer science (2025), pp. 259-274
Closed Access
Reinforcement learning based multi-perspective motion planning of manned electric vertical take-off and landing vehicle in urban environment with wind fields
S. B. Liu, Weizi Li, Haochen Li, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 149, pp. 110392-110392
Closed Access
AI-guided framework for the design of materials and devices for magnetic-tunnel-junction-based true random number generators
Karan Patel, Andrew Maicke, Jared Arzate, et al.
Communications Engineering (2025) Vol. 4, Iss. 1
Open Access
Reinforcement learning applications in water resource management: a systematic literature review
Linus Kåge, Vlatko Milić, Maria Andersson, et al.
Frontiers in Water (2025) Vol. 7
Open Access
Extending Evolution-Guided Policy Gradient Learning into the multi-objective domain
Adam Callaghan, Karl Mason, Patrick Mannion
Neurocomputing (2025), pp. 129991-129991
Open Access
Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021)
Peter Vamplew, Benjamin J. Smith, Johan Källström, et al.
Autonomous Agents and Multi-Agent Systems (2022) Vol. 36, Iss. 2
Open Access | Times Cited: 22
Deep reinforcement learning for adaptive mesh refinement
Corbin Foucart, Aaron Charous, Pierre F. J. Lermusiaux
Journal of Computational Physics (2023) Vol. 491, pp. 112381-112381
Open Access | Times Cited: 14
A constrained multi-objective deep reinforcement learning approach for temperature field optimization of zinc oxide rotary volatile kiln
Fengrun Tang, Zhenxiang Feng, Yonggang Li, et al.
Advanced Engineering Informatics (2023) Vol. 58, pp. 102197-102197
Closed Access | Times Cited: 13
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