Todd Hester
Impact in
- Artificial Intelligence top 2%
- Reinforcement Learning in Robotics
- Evolutionary Algorithms and Applications
- Rehabilitation top 5%
- Stroke Rehabilitation and Recovery
Papers in
-
- Reinforcement Learning in Robotics 18
- Evolutionary Algorithms and Applications 6
- Artificial Intelligence in Games 3
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- Robotic Path Planning Algorithms 7
- Co-authors
- Peter Stone (17 shared papers)Gabriel Dulac-Arnold (4 shared papers)Sven Gowal (1 shared paper)Jerry Li (1 shared paper)Ian Osband (3 shared papers)Joel Z. Leibo (3 shared papers)John Agapiou (3 shared papers)Cosmin Păduraru (1 shared paper)
- Journals
- Machine Learning (2 papers)Proceedings of the IEEE (1 paper)IEEE Pervasive Computing (1 paper)Artificial Intelligence (1 paper)Lecture notes in computer science (4 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Todd Hester
34 papers receiving 1.7k citations
Todd Hester's Hit Papers
Peers
Comparison fields: 5 of 116
- Artificial Intelligence 944
- Rehabilitation 137
- Control and Systems Engineering 426
- Computer Vision and Pattern Recognition 334
- Physical Therapy, Sports Therapy and Rehabilitation 60
Countries citing papers authored by Todd Hester
This map shows the geographic impact of Todd Hester'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 Todd Hester with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Todd Hester more than expected).
Fields of papers citing papers by Todd Hester
This network shows the impact of papers produced by Todd Hester. 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 Todd Hester. The network helps show where Todd Hester may publish in the future.
Co-authors
The 25 scholars most cited alongside Todd Hester, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Deep Q-learning From Demonstrations Hit paper breakdown → | 2018 | 531 |
| 2 | Challenges of real-world reinforcement learning: definitions, benchmarks and analysis Hit paper breakdown → | 2021 | 362 |
| 3 | 2010 | 143 | |
| 4 | 2017 | 136 | |
| 5 | 2012 | 72 | |
| 6 | 2010 | 72 | |
| 7 | 2006 | 70 | |
| 8 | 2015 | 55 | |
| 9 | 2006 | 55 | |
| 10 | 2012 | 53 | |
| 11 | Learning from Demonstrations for Real World Reinforcement Learning | 2017 | 47 |
| 12 | 2009 | 35 | |
| 13 | 2008 | 26 | |
| 14 | 2012 | 24 | |
| 15 | 2008 | 23 | |
| 16 | 2006 | 15 | |
| 17 | 2012 | 15 | |
| 18 | 2010 | 10 | |
| 19 | 2013 | 9 | |
| 20 | Controlled Kicking under Uncertainty | 2010 | 8 |
About Todd Hester
Todd Hester is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Aerospace Engineering, Biomedical Engineering and Automotive Engineering, having authored 34 papers that have together received 1.8k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (18 papers), Robotic Path Planning Algorithms (7 papers), Evolutionary Algorithms and Applications (6 papers), Robotics and Sensor-Based Localization (5 papers), Autonomous Vehicle Technology and Safety (4 papers), Modular Robots and Swarm Intelligence (4 papers), Stroke Rehabilitation and Recovery (4 papers) and Artificial Intelligence in Games (3 papers). The work is most often cited by research in Artificial Intelligence (944 citations), Rehabilitation (137 citations), Control and Systems Engineering (426 citations), Computer Vision and Pattern Recognition (334 citations) and Physical Therapy, Sports Therapy and Rehabilitation (60 citations). Todd Hester has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Peter Stone, Gabriel Dulac-Arnold, Sven Gowal, Jerry Li, Ian Osband, Joel Z. Leibo, John Agapiou, Cosmin Păduraru, Daniel J. Mankowitz and Olivier Pietquin. Their work appears in journals such as Machine Learning, Proceedings of the IEEE, IEEE Pervasive Computing, Artificial Intelligence and Lecture notes in computer science.
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.