Sam Devlin
Impact in
- Artificial Intelligence top 2%
- Reinforcement Learning in Robotics
- Artificial Intelligence in Games
- Management Information Systems top 10%
- FinTech, Crowdfunding, Digital Finance
Papers in
-
- Reinforcement Learning in Robotics 36
- Artificial Intelligence in Games 13
- Software 3
- Model-Driven Software Engineering Techniques 3
- Co-authors
- Daniel Kudenko⋆ (30 shared papers)Peter Cowling (15 shared papers)Enda Howley (4 shared papers)Patrick Mannion (4 shared papers)Jim Duggan (4 shared papers)Anders Drachen (3 shared papers)Joanna Hodge (5 shared papers)Marek Grześ (3 shared papers)
- Journals
- The Knowledge Engineering Review (5 papers)Nature (1 paper)Software & Systems Modeling (1 paper)Connection Science (1 paper)Journal of Business Research (1 paper)
- Partner nations
- United KingdomUnited StatesIreland
In The Last Decade
Sam Devlin
66 papers receiving 1k citations
Peers
Comparison fields: 5 of 68
- Artificial Intelligence 613
- Management Information Systems 66
- Marketing 55
- Software 24
- Computer Science Applications 16
Countries citing papers authored by Sam Devlin
This map shows the geographic impact of Sam Devlin'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 Sam Devlin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sam Devlin more than expected).
Fields of papers citing papers by Sam Devlin
This network shows the impact of papers produced by Sam Devlin. 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 Sam Devlin. The network helps show where Sam Devlin may publish in the future.
Co-authors
The 25 scholars most cited alongside Sam Devlin, 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 68 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 93 | |
| 2 | 2012 | 83 | |
| 3 | 2019 | 82 | |
| 4 | 2015 | 67 | |
| 5 | 2011 | 56 | |
| 6 | 2011 | 52 | |
| 7 | 2014 | 52 | |
| 8 | 2015 | 52 | |
| 9 | 2018 | 48 | |
| 10 | 2018 | 45 | |
| 11 | 2017 | 35 | |
| 12 | 2015 | 28 | |
| 13 | 2016 | 23 | |
| 14 | 2016 | 21 | |
| 15 | 2016 | 21 | |
| 16 | 2019 | 18 | |
| 17 | 2015 | 17 | |
| 18 | 2019 | 17 | |
| 19 | 2016 | 15 | |
| 20 | 2018 | 15 |
About Sam Devlin
Sam Devlin is a scholar working on Artificial Intelligence, Software, Marketing, Computer Science Applications and Strategy and Management, having authored 68 papers that have together received 1.1k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (36 papers), Artificial Intelligence in Games (13 papers), Digital Games and Media (6 papers), Customer churn and segmentation (3 papers), Model-Driven Software Engineering Techniques (3 papers), Social Robot Interaction and HRI (2 papers), Business Strategies and Innovation (2 papers) and Educational Games and Gamification (2 papers). The work is most often cited by research in Artificial Intelligence (613 citations), Management Information Systems (66 citations), Marketing (55 citations), Software (24 citations) and Computer Science Applications (16 citations). Sam Devlin has collaborated with scholars based in United Kingdom, United States and Ireland. Frequent co-authors include Daniel Kudenko⋆, Peter Cowling, Enda Howley, Patrick Mannion, Jim Duggan, Anders Drachen, Joanna Hodge, Marek Grześ, Florian Block and Ann Nowé. Their work appears in journals such as The Knowledge Engineering Review, Nature, Software & Systems Modeling, Connection Science and Journal of Business Research.
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.