Mark H. M. Winands
- Artificial Intelligence top 2%
- Artificial Intelligence in Games 66
- Reinforcement Learning in Robotics 7
- Evolutionary Algorithms and Applications 6
- Economics and Econometrics top 5%
- Sports Analytics and Performance 30
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- Digital Games and Media 37
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- Educational Games and Gamification 7
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- Video Analysis and Summarization 13
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- Gambling Behavior and Treatments 8
- Co-authors
- J.W.H.M. UiterwijkH.J. van den HerikGuillaume ChaslotBruno BouzyMaarten P. D. SchaddYngvi BjörnssonMarc LanctotHendrik Baier
- Partner nations
- NetherlandsFranceIceland
In The Last Decade
Mark H. M. Winands
76 papers receiving 781 citations
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 759
- Economics and Econometrics 297
- Sociology and Political Science 317
- Developmental and Educational Psychology 90
- Computer Vision and Pattern Recognition 131
Countries citing papers authored by Mark H. M. Winands
This map shows the geographic impact of Mark H. M. Winands'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 Mark H. M. Winands with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark H. M. Winands more than expected).
Fields of papers citing papers by Mark H. M. Winands
This network shows the impact of papers produced by Mark H. M. Winands. 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 Mark H. M. Winands. The network helps show where Mark H. M. Winands may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mark H. M. Winands, 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 | 2025 | 0 | |
| 2 | 2023 | 0 | |
| 3 | 2022 | 0 | |
| 4 | 2021 | 1 | |
| 5 | 2020 | 3 | |
| 6 | Representation in Evolutionary Computation for Games | 2019 | 1 |
| 7 | 2018 | 18 | |
| 8 | 2016 | 21 | |
| 9 | Optimizing Propositional Networks. | 2016 | 2 |
| 10 | 2016 | 5 | |
| 11 | Neural Networks for Video Game AI | 2015 | 1 |
| 12 | 2014 | 4 | |
| 13 | 2013 | 5 | |
| 14 | 2013 | 4 | |
| 15 | 2013 | 0 | |
| 16 | Playout search for Monte-Carlo tree search in multi-player games | 2012 | 2 |
| 17 | 2012 | 17 | |
| 18 | 2008 | 4 | |
| 19 | 2007 | 4 | |
| 20 | 2003 | 3 |
About Mark H. M. Winands
Mark H. M. Winands is a scholar working on Artificial Intelligence, Economics and Econometrics and Sociology and Political Science, having authored 89 papers that have together received 863 indexed citations. Recurring topics across this work include Artificial Intelligence in Games (66 papers), Digital Games and Media (37 papers), Sports Analytics and Performance (30 papers), Video Analysis and Summarization (13 papers), Gambling Behavior and Treatments (8 papers), Reinforcement Learning in Robotics (7 papers), Educational Games and Gamification (7 papers) and Evolutionary Algorithms and Applications (6 papers). The work is most often cited by research in Artificial Intelligence (759 citations), Economics and Econometrics (297 citations) and Sociology and Political Science (317 citations). Mark H. M. Winands has collaborated with scholars based in Netherlands, France and Iceland. Frequent co-authors include J.W.H.M. Uiterwijk, H.J. van den Herik, Guillaume Chaslot, Bruno Bouzy, Maarten P. D. Schadd, Yngvi Björnsson, Marc Lanctot, Hendrik Baier, István Szita and Jialin Liu. Their work appears in journals such as Information Sciences, Artificial Intelligence and Machine Learning.
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.