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 16
- Evolutionary Algorithms and Applications 6
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- Robotic Path Planning Algorithms 5
- Co-authors
- Peter Stone (13 shared papers)Gabriel Dulac-Arnold (4 shared papers)Cosmin Păduraru (1 shared paper)Nir Levine (2 shared papers)Daniel J. Mankowitz (2 shared papers)Jerry Li (1 shared paper)Sven Gowal (1 shared paper)Audrūnas Gruslys (3 shared papers)
- Journals
- Machine Learning (2 papers)IEEE Pervasive Computing (1 paper)Proceedings of the IEEE (1 paper)Artificial Intelligence (1 paper)Studies in computational intelligence (1 paper)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Todd Hester
29 papers receiving 1.6k citations
Todd Hester's Hit Papers
Peers
Comparison fields: 5 of 112
- Artificial Intelligence 830
- Rehabilitation 134
- Control and Systems Engineering 394
- Computer Vision and Pattern Recognition 288
- Physical Therapy, Sports Therapy and Rehabilitation 55
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 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Deep Q-learning From Demonstrations Hit paper breakdown → | 2018 | 493 |
| 2 | Challenges of real-world reinforcement learning: definitions, benchmarks and analysis Hit paper breakdown → | 2021 | 345 |
| 3 | 2010 | 133 | |
| 4 | 2017 | 124 | |
| 5 | 2006 | 67 | |
| 6 | 2012 | 64 | |
| 7 | 2010 | 63 | |
| 8 | 2015 | 52 | |
| 9 | 2006 | 49 | |
| 10 | Learning from Demonstrations for Real World Reinforcement Learning | 2017 | 44 |
| 11 | 2012 | 44 | |
| 12 | 2009 | 33 | |
| 13 | 2008 | 24 | |
| 14 | 2008 | 18 | |
| 15 | 2006 | 15 | |
| 16 | 2012 | 15 | |
| 17 | 2010 | 8 | |
| 18 | 2008 | 7 | |
| 19 | 2013 | 6 | |
| 20 | 2006 | 5 |
About Todd Hester
Todd Hester is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Rehabilitation, Aerospace Engineering and Biomedical Engineering, having authored 29 papers that have together received 1.6k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (16 papers), Evolutionary Algorithms and Applications (6 papers), Robotic Path Planning Algorithms (5 papers), Stroke Rehabilitation and Recovery (4 papers), Robotics and Sensor-Based Localization (4 papers), Modular Robots and Swarm Intelligence (3 papers), Neurological disorders and treatments (3 papers) and Parkinson's Disease Mechanisms and Treatments (3 papers). The work is most often cited by research in Artificial Intelligence (830 citations), Rehabilitation (134 citations), Control and Systems Engineering (394 citations), Computer Vision and Pattern Recognition (288 citations) and Physical Therapy, Sports Therapy and Rehabilitation (55 citations). Todd Hester has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Peter Stone, Gabriel Dulac-Arnold, Cosmin Păduraru, Nir Levine, Daniel J. Mankowitz, Jerry Li, Sven Gowal, Audrūnas Gruslys, John Agapiou and Marc Lanctot. Their work appears in journals such as Machine Learning, IEEE Pervasive Computing, Proceedings of the IEEE, Artificial Intelligence and Studies in computational intelligence.
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.