Riad Akrour

532 total citations
13 papers, 139 citations indexed

About

Riad Akrour is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Riad Akrour has authored 13 papers receiving a total of 139 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 6 papers in Control and Systems Engineering and 4 papers in Computational Theory and Mathematics. Recurrent topics in Riad Akrour's work include Reinforcement Learning in Robotics (11 papers), Robot Manipulation and Learning (5 papers) and Advanced Bandit Algorithms Research (3 papers). Riad Akrour is often cited by papers focused on Reinforcement Learning in Robotics (11 papers), Robot Manipulation and Learning (5 papers) and Advanced Bandit Algorithms Research (3 papers). Riad Akrour collaborates with scholars based in Germany, United Kingdom and Japan. Riad Akrour's co-authors include Gerhard Neumann, Jan Peters, Christian Wirth, Johannes Fürnkranz, Filipe Veiga, Joni Pajarinen, Yang Weng, Toshihiro Maki, Takumi Matsuda and Marc Schoenauer and has published in prestigious journals such as Machine Learning, Journal of Machine Learning Research and IEEE Journal of Oceanic Engineering.

In The Last Decade

Riad Akrour

12 papers receiving 132 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Riad Akrour Germany 8 93 56 28 20 18 13 139
Manuel Watter Germany 2 82 0.9× 32 0.6× 53 1.9× 7 0.3× 7 0.4× 3 133
Piotr Dziwiński Poland 4 43 0.5× 28 0.5× 7 0.3× 8 0.4× 19 1.1× 6 113
Bernhard Hengst Australia 7 127 1.4× 36 0.6× 29 1.0× 3 0.1× 8 0.4× 19 183
Chen Tessler Israel 5 104 1.1× 33 0.6× 39 1.4× 3 0.1× 12 0.7× 10 165
Chenjia Bai China 6 94 1.0× 41 0.7× 27 1.0× 2 0.1× 25 1.4× 26 173
Torsten Koller Germany 4 85 0.9× 136 2.4× 27 1.0× 7 0.3× 15 0.8× 6 205
Nicholas Rhinehart United States 7 84 0.9× 35 0.6× 104 3.7× 5 0.3× 6 0.3× 17 166
William Uther Australia 6 122 1.3× 21 0.4× 29 1.0× 3 0.1× 8 0.4× 9 183
Nashwa Ahmad Kamal Egypt 8 49 0.5× 75 1.3× 46 1.6× 4 0.2× 29 1.6× 55 193
Jacob Menick United Kingdom 4 120 1.3× 11 0.2× 61 2.2× 4 0.2× 33 1.8× 6 173

Countries citing papers authored by Riad Akrour

Since Specialization
Citations

This map shows the geographic impact of Riad Akrour'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 Riad Akrour with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Riad Akrour more than expected).

Fields of papers citing papers by Riad Akrour

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Riad Akrour. 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 Riad Akrour. The network helps show where Riad Akrour may publish in the future.

Co-authorship network of co-authors of Riad Akrour

This figure shows the co-authorship network connecting the top 25 collaborators of Riad Akrour. A scholar is included among the top collaborators of Riad Akrour 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 Riad Akrour. Riad Akrour is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
Weng, Yang, Joni Pajarinen, Riad Akrour, et al.. (2022). Reinforcement Learning Based Underwater Wireless Optical Communication Alignment for Autonomous Underwater Vehicles. IEEE Journal of Oceanic Engineering. 47(4). 1231–1245. 22 indexed citations
2.
Akrour, Riad, Joni Pajarinen, Jan Peters, & Gerhard Neumann. (2022). Projections for Approximate Policy Iteration Algorithms. Lincoln Repository (University of Lincoln). 181–190.
3.
Veiga, Filipe, Riad Akrour, & Jan Peters. (2020). Hierarchical Tactile-Based Control Decomposition of Dexterous In-Hand Manipulation Tasks. Frontiers in Robotics and AI. 7. 521448–521448. 10 indexed citations
4.
Pajarinen, Joni, et al.. (2019). Compatible natural gradient policy search. Machine Learning. 108(8-9). 1443–1466. 13 indexed citations
5.
Peters, Jan, et al.. (2019). Learning Replanning Policies With Direct Policy Search. IEEE Robotics and Automation Letters. 4(2). 2196–2203. 2 indexed citations
6.
Akrour, Riad, Filipe Veiga, Jan Peters, & Gerhard Neumann. (2018). Regularizing Reinforcement Learning with State Abstraction. 534–539. 11 indexed citations
7.
Pinsler, Robert, Riad Akrour, Takayuki Osa, Jan Peters, & Gerhard Neumann. (2018). Sample and Feedback Efficient Hierarchical Reinforcement Learning from Human Preferences. Lincoln Repository (University of Lincoln). 596–601. 8 indexed citations
8.
Akrour, Riad, Dmitry V. Sorokin, Jan Peters, & Gerhard Neumann. (2017). Local Bayesian optimization of motor skills. Lincoln Repository (University of Lincoln). 41–50. 4 indexed citations
9.
Akrour, Riad, et al.. (2017). Empowered skills. 1. 6435–6441. 3 indexed citations
10.
Akrour, Riad, et al.. (2017). Layered direct policy search for learning hierarchical skills. 13. 6442–6448. 6 indexed citations
11.
Wirth, Christian, Riad Akrour, Gerhard Neumann, & Johannes Fürnkranz. (2017). A survey of preference-based reinforcement learning methods. Journal of Machine Learning Research. 18(1). 4945–4990. 37 indexed citations
12.
Akrour, Riad, et al.. (2016). Model-free Trajectory Optimization for Reinforcement Learning. Lincoln Repository (University of Lincoln). 2961–2970. 8 indexed citations
13.
Schoenauer, Marc, et al.. (2014). Programming by Feedback. International Conference on Machine Learning. 1503–1511. 15 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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