Bei Peng

736 total citations
18 papers, 199 citations indexed

About

Bei Peng is a scholar working on Artificial Intelligence, Control and Systems Engineering and Information Systems. According to data from OpenAlex, Bei Peng has authored 18 papers receiving a total of 199 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 4 papers in Control and Systems Engineering and 3 papers in Information Systems. Recurrent topics in Bei Peng's work include Reinforcement Learning in Robotics (10 papers), Software Engineering Research (3 papers) and Robot Manipulation and Learning (3 papers). Bei Peng is often cited by papers focused on Reinforcement Learning in Robotics (10 papers), Software Engineering Research (3 papers) and Robot Manipulation and Learning (3 papers). Bei Peng collaborates with scholars based in United States, United Kingdom and Netherlands. Bei Peng's co-authors include Matthew E. Taylor, James MacGlashan, Robert Loftin, David L. Roberts, Michael L. Littman, Jeff Huang, Mark K. Ho, Guan Wang, Jivko Sinapov and Matteo Leonetti and has published in prestigious journals such as Applied Energy, Journal of Machine Learning Research and Autonomous Agents and Multi-Agent Systems.

In The Last Decade

Bei Peng

15 papers receiving 185 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bei Peng United States 8 159 61 21 14 13 18 199
Bruno Castro da Silva United States 7 114 0.7× 39 0.6× 34 1.6× 9 0.6× 9 0.7× 16 204
Alberto Maria Metelli Italy 7 109 0.7× 43 0.7× 22 1.0× 26 1.9× 11 0.8× 32 205
Bilal Piot France 3 89 0.6× 47 0.8× 20 1.0× 12 0.9× 5 0.4× 5 132
Alexander Sasha Vezhnevets United Kingdom 4 107 0.7× 33 0.5× 27 1.3× 16 1.1× 4 0.3× 6 140
André Barreto United States 8 176 1.1× 46 0.8× 21 1.0× 19 1.4× 5 0.4× 16 223
Mark Ring Switzerland 8 141 0.9× 27 0.4× 33 1.6× 8 0.6× 10 0.8× 13 167
Riad Akrour Germany 8 93 0.6× 56 0.9× 28 1.3× 11 0.8× 5 0.4× 13 139
Juan Carlos Santamaria United States 4 211 1.3× 57 0.9× 35 1.7× 14 1.0× 4 0.3× 8 260
Justin Fu United States 6 96 0.6× 35 0.6× 33 1.6× 13 0.9× 6 0.5× 14 145
Daniel Hládek Slovakia 9 194 1.2× 51 0.8× 40 1.9× 17 1.2× 13 1.0× 50 295

Countries citing papers authored by Bei Peng

Since Specialization
Citations

This map shows the geographic impact of Bei Peng's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bei Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bei Peng more than expected).

Fields of papers citing papers by Bei Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bei Peng. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bei Peng. The network helps show where Bei Peng may publish in the future.

Co-authorship network of co-authors of Bei Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Bei Peng. A scholar is included among the top collaborators of Bei Peng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bei Peng. Bei Peng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Peng, Bei, et al.. (2025). Evaluating the Evaluation of Diversity in Commonsense Generation. 24258–24275.
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Peng, Bei. (2022). Chinese music under the background of cultural globalization. 9(1-2). 99–108. 5 indexed citations
6.
Iqbal, Shariq, et al.. (2021). Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning. Research Repository (Delft University of Technology). 139. 4596–4606. 7 indexed citations
7.
Narvekar, Sanmit, Bei Peng, Matteo Leonetti, et al.. (2020). Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey. Journal of Machine Learning Research. 21(181). 1–50. 18 indexed citations
8.
Peng, Bei, James MacGlashan, Robert Loftin, et al.. (2018). Curriculum Design for Machine Learners in Sequential Decision Tasks. IEEE Transactions on Emerging Topics in Computational Intelligence. 2(4). 268–277. 5 indexed citations
9.
Peng, Bei, James MacGlashan, Robert Loftin, et al.. (2017). Curriculum Design for Machine Learners in Sequential Decision Tasks. Adaptive Agents and Multi-Agents Systems. 1682–1684. 3 indexed citations
10.
MacGlashan, James, Mark K. Ho, Robert Loftin, et al.. (2017). Interactive Learning from Policy-Dependent Human Feedback. arXiv (Cornell University). 2285–2294. 40 indexed citations
11.
Peng, Bei, James MacGlashan, Robert Loftin, et al.. (2016). A Need for Speed: Adapting Agent Action Speed to Improve Task Learning from Non-Expert Humans. Adaptive Agents and Multi-Agents Systems. 957–965. 16 indexed citations
12.
Peng, Bei, et al.. (2015). Generating real-time crowd advice to improve reinforcement learning agents. National Conference on Artificial Intelligence. 2 indexed citations
13.
Loftin, Robert, Bei Peng, James MacGlashan, et al.. (2015). Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning. Autonomous Agents and Multi-Agent Systems. 30(1). 30–59. 43 indexed citations
14.
Scott, Mitchell G., et al.. (2015). On the Ability to Provide Demonstrations on a UAS: Observing 90 Untrained Participants Abusing a Flying Robot. Maryland Shared Open Access Repository (USMAI Consortium). 117–121. 1 indexed citations
15.
Peng, Bei, et al.. (2015). Towards Integrating Real-Time Crowd Advice with Reinforcement Learning. 17–20. 4 indexed citations
16.
MacGlashan, James, Michael L. Littman, Robert Loftin, et al.. (2014). Training an Agent to Ground Commands with Reward and Punishment. 5 indexed citations
17.
Loftin, Robert, James MacGlashan, Bei Peng, et al.. (2014). A Strategy-Aware Technique for Learning Behaviors from Discrete Human Feedback. Proceedings of the AAAI Conference on Artificial Intelligence. 28(1). 29 indexed citations
18.
Loftin, Robert, Bei Peng, James MacGlashan, et al.. (2014). Learning something from nothing: Leveraging implicit human feedback strategies. 607–612. 14 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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