Peter Stone
- Artificial Intelligence top 0.05%
- Reinforcement Learning in Robotics 179
- Multi-Agent Systems and Negotiation 53
- Evolutionary Algorithms and Applications 45
- Transportation top 0.2%
- Control and Systems Engineering top 0.1%
- Robot Manipulation and Learning 43
- Traffic control and management 35
- Automotive Engineering top 0.2%
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- Auction Theory and Applications 38
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- Robotic Path Planning Algorithms 62
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- Modular Robots and Swarm Intelligence 30
- Co-authors
- Kurt DresnerMatthew E. TaylorManuela VelosoW. Bradley KnoxNate KohlShimon WhitesonTsz-Chiu AuXuesu Xiao
- Journals
- Artificial Intelligence (11 papers)IEEE Robotics and Automation Letters (9 papers)Autonomous Agents and Multi-Agent Systems (8 papers)
- Partner nations
- United StatesUnited KingdomIsrael
In The Last Decade
Peter Stone
425 papers receiving 12.4k citations
Hit Papers
Peers
Comparison fields: 5 of 175
- Artificial Intelligence 7.0k
- Transportation 1.4k
- Control and Systems Engineering 3.9k
- Automotive Engineering 1.9k
- Management Science and Operations Research 1.5k
Countries citing papers authored by Peter Stone
This map shows the geographic impact of Peter Stone'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 Stone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Stone more than expected).
Fields of papers citing papers by Peter Stone
This network shows the impact of papers produced by Peter Stone. 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 Stone. The network helps show where Peter Stone may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Peter Stone, 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 | 2024 | 5 | |
| 2 | 2024 | 3 | |
| 3 | 2023 | 6 | |
| 4 | 2022 | 20 | |
| 5 | 2022 | 33 | |
| 6 | 2022 | 8 | |
| 7 | 2021 | 1 | |
| 8 | 2021 | 34 | |
| 9 | 2021 | 30 | |
| 10 | 2020 | 1 | |
| 11 | 2019 | 17 | |
| 12 | 2019 | 5 | |
| 13 | 2019 | 4 | |
| 14 | 2018 | 2 | |
| 15 | 2018 | 9 | |
| 16 | 2014 | 1 | |
| 17 | Efficient Selection of Multiple Bandit Arms: Theory and Practice | 2010 | 29 |
| 18 | 2009 | 1 | |
| 19 | 2006 | 1 | |
| 20 | 2004 | 4 |
About Peter Stone
Peter Stone is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 443 papers that have together received 13.3k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (179 papers), Robotic Path Planning Algorithms (62 papers), Multi-Agent Systems and Negotiation (53 papers), Evolutionary Algorithms and Applications (45 papers), Robot Manipulation and Learning (43 papers), Auction Theory and Applications (38 papers), Traffic control and management (35 papers) and Modular Robots and Swarm Intelligence (30 papers). The work is most often cited by research in Artificial Intelligence (7.0k citations), Transportation (1.4k citations) and Control and Systems Engineering (3.9k citations). Peter Stone has collaborated with scholars based in United States, United Kingdom and Israel. Frequent co-authors include Kurt Dresner, Matthew E. Taylor, Manuela Veloso, W. Bradley Knox, Nate Kohl, Shimon Whiteson, Tsz-Chiu Au, Xuesu Xiao, Todd Hester and David Pardoe. Their work appears in journals such as Artificial Intelligence, IEEE Robotics and Automation Letters, Autonomous Agents and Multi-Agent Systems, Autonomous Robots and AI Magazine.
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.