Todd Hester
- Artificial Intelligence top 2%
- Reinforcement Learning in Robotics 16
- Evolutionary Algorithms and Applications 6
- Rehabilitation top 5%
- Stroke Rehabilitation and Recovery 4
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- Robotic Path Planning Algorithms 5
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- Robotics and Sensor-Based Localization 4
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- Modular Robots and Swarm Intelligence 3
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- Neurological disorders and treatments 3
- Parkinson's Disease Mechanisms and Treatments 3
Todd Hester
29 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 111
- Artificial Intelligence 816
- Rehabilitation 142
- Control and Systems Engineering 385
- Physical Therapy, Sports Therapy and Rehabilitation 65
- Computer Vision and Pattern Recognition 289
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-authorship network
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
| # | Work | ||
|---|---|---|---|
| 1 | Challenges of real-world reinforcement learning: definitions, benchmarks and analysisbreakdown → | 2021 | 320 |
| 2 | Robust Reinforcement Learning for Continuous Control with Model Misspecification | 2020 | 1 |
| 3 | Learning from Demonstrations for Real World Reinforcement Learning | 2017 | 43 |
| 4 | 2015 | 51 | |
| 5 | 2013 | 6 | |
| 6 | TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots | 2012 | 2 |
| 7 | Designing intelligent robots : reintegrating AI : papers from the AAAI Spring Symposium | 2012 | 4 |
| 8 | 2012 | 15 | |
| 9 | 2012 | 42 | |
| 10 | 2010 | 133 | |
| 11 | Controlled Kicking under Uncertainty | 2010 | 4 |
| 12 | 2010 | 60 | |
| 13 | 2009 | 33 | |
| 14 | 2008 | 7 | |
| 15 | 2008 | 18 | |
| 16 | UT Austin Villa 2008: Standing On Two Legs | 2008 | 3 |
| 17 | 2007 | 2 | |
| 18 | 2006 | 15 | |
| 19 | 2006 | 3 | |
| 20 | 2006 | 49 |
About Todd Hester
Todd Hester is a scholar working on Rehabilitation, Artificial Intelligence and Physical Therapy, Sports Therapy and Rehabilitation, 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 (816 citations), Rehabilitation (142 citations) and Control and Systems Engineering (385 citations). Todd Hester has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Peter Stone, Gabriel Dulac-Arnold, Tom Schaul, Ian Osband, Marc Lanctot, Joel Z. Leibo, Audrūnas Gruslys, John Agapiou, Olivier Pietquin and Jerry Li. Their work appears in journals such as Machine Learning, Artificial Intelligence, Proceedings of the IEEE, IEEE Pervasive Computing 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.