Rob Powers
Impact in
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- Game Theory and Applications
- Auction Theory and Applications
- Advanced Bandit Algorithms Research
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
Papers in
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- Reinforcement Learning in Robotics 9
- Artificial Intelligence in Games 2
- Fuzzy Logic and Control Systems 1
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- Game Theory and Applications 6
- Auction Theory and Applications 3
- Advanced Bandit Algorithms Research 2
- Co-authors
- Yoav Shoham (9 shared papers)Trond Grenager (4 shared papers)Illah Nourbakhsh (1 shared paper)Stan Birchfield (1 shared paper)Ira L. Cohen (1 shared paper)Moisés Goldszmidt (1 shared paper)Maxsim Gibiansky (1 shared paper)Sara Kianian (1 shared paper)
- Journals
- AI Magazine (1 paper)Artificial Intelligence (1 paper)Machine Learning (1 paper)Science Translational Medicine (1 paper)International Joint Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesFranceAustralia
In The Last Decade
Rob Powers
13 papers receiving 962 citations
Peers
Comparison fields: 5 of 89
- Management Science and Operations Research 329
- Artificial Intelligence 486
- General Decision Sciences 16
- Safety Research 68
- Computer Vision and Pattern Recognition 172
Countries citing papers authored by Rob Powers
This map shows the geographic impact of Rob Powers'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 Rob Powers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rob Powers more than expected).
Fields of papers citing papers by Rob Powers
This network shows the impact of papers produced by Rob Powers. 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 Rob Powers. The network helps show where Rob Powers may publish in the future.
Co-authors
The 15 scholars most cited alongside Rob Powers, 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 | 2007 | 268 | |
| 2 | 1995 | 217 | |
| 3 | Multi-Agent Reinforcement Learning:a critical survey | 2003 | 182 |
| 4 | 2021 | 141 | |
| 5 | New Criteria and a New Algorithm for Learning in Multi-Agent Systems | 2004 | 75 |
| 6 | 2005 | 55 | |
| 7 | Learning against opponents with bounded memory | 2005 | 54 |
| 8 | 2006 | 32 | |
| 9 | 2002 | 31 | |
| 10 | On the Agenda(s) of Research on Multi-Agent Learning. | 2004 | 17 |
| 11 | 2006 | 12 | |
| 12 | Quantization Errors in Computer-Generated Holograms. | 1975 | 2 |
| 13 | 2010 | 1 |
About Rob Powers
Rob Powers is a scholar working on Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications, Neurology and Control and Systems Engineering, having authored 13 papers that have together received 1.1k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (9 papers), Game Theory and Applications (6 papers), Auction Theory and Applications (3 papers), Artificial Intelligence in Games (2 papers), Advanced Bandit Algorithms Research (2 papers), Robotics and Sensor-Based Localization (1 paper), Fuzzy Logic and Control Systems (1 paper) and Neurological disorders and treatments (1 paper). The work is most often cited by research in Management Science and Operations Research (329 citations), Artificial Intelligence (486 citations), General Decision Sciences (16 citations), Safety Research (68 citations) and Computer Vision and Pattern Recognition (172 citations). Rob Powers has collaborated with scholars based in United States, France and Australia. Frequent co-authors include Yoav Shoham, Trond Grenager, Illah Nourbakhsh, Stan Birchfield, Ira L. Cohen, Moisés Goldszmidt, Maxsim Gibiansky, Sara Kianian, Adeeti V. Ullal and Dan Trietsch. Their work appears in journals such as AI Magazine, Artificial Intelligence, Machine Learning, Science Translational Medicine and International Joint Conference on Artificial 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.