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Reinforcement Learning in Robotics
TopicLeading institutions, researchers & key papers
This cluster of papers encompasses a wide range of advancements in reinforcement learning algorithms and their applications, including deep learning, neural networks, robotics, autonomous control, policy gradient methods, multi-agent systems, model-based learning, curiosity-driven exploration, and simulation to real-world transfer.
51
Works
IDs:OpenAlex
How has Reinforcement Learning in Robotics's publication output changed over time?
ScholarIQpublication output · 2013–2025
Output grew0% over the shown period — from 1 works in 2013 to 1 in 2025.
1
1
2
3
1
2
1
1
20132017201820202021202220242025
What are the most-cited papers on Reinforcement Learning in Robotics?
ScholarIQmost cited works
Collaborative Robot-Assisted Endovascular Catheterization with Generative Adversarial Imitation Learning
Wenqiang Chi, Giulio Dagnino, Trevor M. Y. Kwok, Anh Nguyen, Dennis Kundrat, Mohamed E. M. K. Abdelaziz, Celia Riga, Colin Bicknell, Guang‐Zhong Yang
2020109 Citations
A game-theoretic model and best-response learning method for ad hoc coordination in multiagent systems
Stefano V. Albrecht, Subramanian Ramamoorthy
arXiv (Cornell University). 201372 CitationsOPEN ACCESS
Human, I wrote a song for you: An experiment testing the influence of machines’ attributes on the AI-composed music evaluation
Joo-Wha Hong, Katrin Fischer, Yul Ha, Yilei Zeng
Computers in Human Behavior. 202262 Citations
First Order Constrained Optimization in Policy Space
Yiming Zhang, Quan Vuong, Keith W. Ross
arXiv (Cornell University). 202052 CitationsOPEN ACCESS
Playing 20 Question Game with Policy-Based Reinforcement Learning
Huang Hu, Xianchao Wu, Bingfeng Luo, Chongyang Tao, Can Xu, Wei Biao Wu, Zhan Chen
201826 CitationsOPEN ACCESS
Where is Reinforcement Learning in Robotics research published, and who funds it?
ScholarIQvenues & funding sources
TOP JOURNALS
TOP FUNDERS
National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
Funder breakdown is a member featureSign up free to unlock
How much of the research on Reinforcement Learning in Robotics is open access?
ScholarIQopen access share
67%OPEN ACCESS
Gold
17%
Green
50%
Hybrid
0%
Bronze
0%
Closed
33%
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