Riad Akrour
- Artificial Intelligence top 10%
- Reinforcement Learning in Robotics 11
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- Robot Manipulation and Learning 5
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- Robotic Path Planning Algorithms 2
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- Advanced Bandit Algorithms Research 3
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- Adaptive Dynamic Programming Control 2
- Advanced Multi-Objective Optimization Algorithms 1
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- Motor Control and Adaptation 1
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- Indoor and Outdoor Localization Technologies 1
- Co-authors
- Gerhard NeumannJan PetersChristian WirthJohannes FürnkranzFilipe VeigaJoni PajarinenYang WengToshihiro Maki
- Cited by
- Artificial IntelligenceControl and Systems EngineeringComputer Vision and Pattern Recognition
- Journals
- Machine Learning (1 paper)Journal of Machine Learning Research (1 paper)IEEE Journal of Oceanic Engineering (1 paper)
- Partner nations
- GermanyUnited KingdomJapan
In The Last Decade
Riad Akrour
12 papers receiving 132 citations
Peers
Comparison fields: 5 of 35
- Artificial Intelligence 93
- Control and Systems Engineering 56
- Computer Vision and Pattern Recognition 28
- Ocean Engineering 20
- Management Science and Operations Research 11
Countries citing papers authored by Riad Akrour
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
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
The 15 scholars most cited alongside Riad Akrour, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 22 | |
| 2 | 2022 | 0 | |
| 3 | 2020 | 10 | |
| 4 | 2019 | 13 | |
| 5 | 2019 | 2 | |
| 6 | 2018 | 11 | |
| 7 | 2018 | 8 | |
| 8 | Local Bayesian optimization of motor skills | 2017 | 4 |
| 9 | 2017 | 3 | |
| 10 | 2017 | 6 | |
| 11 | 2017 | 37 | |
| 12 | Model-free Trajectory Optimization for Reinforcement Learning | 2016 | 8 |
| 13 | Programming by Feedback | 2014 | 15 |
About Riad Akrour
Riad Akrour is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computational Theory and Mathematics, having authored 13 papers that have together received 139 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (11 papers), Robot Manipulation and Learning (5 papers), Advanced Bandit Algorithms Research (3 papers), Adaptive Dynamic Programming Control (2 papers), Robotic Path Planning Algorithms (2 papers), Motor Control and Adaptation (1 paper), Indoor and Outdoor Localization Technologies (1 paper) and Advanced Multi-Objective Optimization Algorithms (1 paper). The work is most often cited by research in Artificial Intelligence (93 citations), Control and Systems Engineering (56 citations) and Computer Vision and Pattern Recognition (28 citations). Riad Akrour has collaborated with scholars based in Germany, United Kingdom and Japan. Frequent co-authors include Gerhard Neumann, Jan Peters, Christian Wirth, Johannes Fürnkranz, Filipe Veiga, Joni Pajarinen, Yang Weng, Toshihiro Maki, Takumi Matsuda and Marc Schoenauer. Their work appears in journals such as Machine Learning, Journal of Machine Learning Research and IEEE Journal of Oceanic Engineering.
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.