Peter Sunehag
Impact in
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
- Evolutionary Algorithms and Applications
- Artificial Intelligence in Games
- Adversarial Robustness in Machine Learning
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- Distributed Control Multi-Agent Systems
- IoT and Edge/Fog Computing
Papers in
-
- Reinforcement Learning in Robotics 10
- Algorithms and Data Compression 3
- Artificial Intelligence in Games 3
- Evolutionary Algorithms and Applications 3
- Anomaly Detection Techniques and Applications 3
- Co-authors
- Joel Z. LeiboThore GraepelGuy LeverNicolas SonneratMarc LanctotKarl TuylsAudrūnas GruslysVinícius Zambaldi
- Journals
- Journal of Machine Learning Research (2 papers)Behavioral and Brain Sciences (1 paper)Journal of Approximation Theory (1 paper)Journal of Mathematical Analysis and Applications (1 paper)Studia Mathematica (1 paper)
- Partner nations
- AustraliaUnited KingdomSweden
In The Last Decade
Peter Sunehag
22 papers receiving 315 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 218
- Computer Networks and Communications 87
- Computational Theory and Mathematics 60
- Management Science and Operations Research 28
- Computer Vision and Pattern Recognition 44
Countries citing papers authored by Peter Sunehag
This map shows the geographic impact of Peter Sunehag'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 Peter Sunehag with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Sunehag more than expected).
Fields of papers citing papers by Peter Sunehag
This network shows the impact of papers produced by Peter Sunehag. 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 Peter Sunehag. The network helps show where Peter Sunehag may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Peter Sunehag, 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 | 2023 | 8 | |
| 2 | 2022 | 1 | |
| 3 | 2019 | 5 | |
| 4 | 2019 | 4 | |
| 5 | 2019 | 6 | |
| 6 | 2018 | 229 | |
| 7 | Rationality, optimism and guarantees in general reinforcement learning | 2015 | 5 |
| 8 | Reinforcement learning with value advice | 2014 | 0 |
| 9 | Feature Reinforcement Learning: State of the Art | 2014 | 3 |
| 10 | A dual process theory of optimistic cognition | 2014 | 1 |
| 11 | Q-learning for history-based reinforcement learning | 2013 | 7 |
| 12 | Feature Reinforcement Learning using Looping Suffix Trees | 2012 | 2 |
| 13 | Coding of non-stationary sources as a foundation for detecting change points and outliers in binary time-series | 2012 | 1 |
| 14 | 2012 | 1 | |
| 15 | Context tree maximizing reinforcement learning | 2012 | 4 |
| 16 | Emerge and spread models and word burstiness | 2007 | 1 |
| 17 | 2007 | 2 | |
| 18 | 2004 | 2 | |
| 19 | 2003 | 2 | |
| 20 | Interpolation of Subcouples, New Results and Applications | 2003 | 2 |
About Peter Sunehag
Peter Sunehag is a scholar working on Artificial Intelligence, Management Science and Operations Research, Applied Mathematics, Signal Processing and Mathematical Physics, having authored 26 papers that have together received 333 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (10 papers), Advanced Harmonic Analysis Research (4 papers), Algorithms and Data Compression (3 papers), Time Series Analysis and Forecasting (3 papers), Artificial Intelligence in Games (3 papers), Holomorphic and Operator Theory (3 papers), Evolutionary Algorithms and Applications (3 papers) and Anomaly Detection Techniques and Applications (3 papers). The work is most often cited by research in Artificial Intelligence (218 citations), Computer Networks and Communications (87 citations), Computational Theory and Mathematics (60 citations), Management Science and Operations Research (28 citations) and Computer Vision and Pattern Recognition (44 citations). Peter Sunehag has collaborated with scholars based in Australia, United Kingdom and Sweden. Frequent co-authors include Joel Z. Leibo, Thore Graepel, Guy Lever, Nicolas Sonnerat, Marc Lanctot, Karl Tuyls, Audrūnas Gruslys, Vinícius Zambaldi, Wojciech Marian Czarnecki and Max Jaderberg. Their work appears in journals such as Journal of Machine Learning Research, Behavioral and Brain Sciences, Journal of Approximation Theory, Journal of Mathematical Analysis and Applications and Studia Mathematica.
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.