Daniel Kudenko⋆
Impact in
- Artificial Intelligence top 1%
- Reinforcement Learning in Robotics
- Evolutionary Algorithms and Applications
- Artificial Intelligence in Games
- Multi-Agent Systems and Negotiation
- Metaheuristic Optimization Algorithms Research
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- Auction Theory and Applications
Papers in
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- Reinforcement Learning in Robotics 57
- Evolutionary Algorithms and Applications 23
- Artificial Intelligence in Games 22
- Multi-Agent Systems and Negotiation 11
- Data Stream Mining Techniques 7
- Metaheuristic Optimization Algorithms Research 7
- Co-authors
- Sam Devlin (30 shared papers)Marek Grześ (15 shared papers)Kleanthis Malialis (4 shared papers)Eduardo Alonso (5 shared papers)Dimitar Lubomirov Kazakov (8 shared papers)Peter Cowling (7 shared papers)G. Flucke (1 shared paper)Mark d’Inverno (1 shared paper)
- Journals
- The Knowledge Engineering Review (6 papers)Lecture notes in computer science (28 papers)Neural Computing and Applications (3 papers)Connection Science (2 papers)Engineering Applications of Artificial Intelligence (2 papers)
- Partner nations
- United KingdomGermanyUnited States
In The Last Decade
Daniel Kudenko⋆
150 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 126
- Artificial Intelligence 1.3k
- Management Science and Operations Research 298
- Computer Networks and Communications 416
- Computational Theory and Mathematics 253
- Management Information Systems 116
Countries citing papers authored by Daniel Kudenko⋆
This map shows the geographic impact of Daniel Kudenko⋆'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 Daniel Kudenko⋆ with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Kudenko⋆ more than expected).
Fields of papers citing papers by Daniel Kudenko⋆
This network shows the impact of papers produced by Daniel Kudenko⋆. 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 Daniel Kudenko⋆. The network helps show where Daniel Kudenko⋆ may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Kudenko⋆, 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 160 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 134 | |
| 2 | 2001 | 113 | |
| 3 | 2017 | 91 | |
| 4 | 2012 | 82 | |
| 5 | 2015 | 61 | |
| 6 | 2011 | 58 | |
| 7 | 2008 | 56 | |
| 8 | 2011 | 52 | |
| 9 | 2014 | 52 | |
| 10 | 2015 | 50 | |
| 11 | 2010 | 48 | |
| 12 | 2007 | 47 | |
| 13 | 2003 | 47 | |
| 14 | 2014 | 45 | |
| 15 | 2008 | 41 | |
| 16 | 2010 | 39 | |
| 17 | 2019 | 38 | |
| 18 | 2007 | 35 | |
| 19 | 2004 | 33 | |
| 20 | 2019 | 29 |
About Daniel Kudenko⋆
Daniel Kudenko⋆ is a scholar working on Artificial Intelligence, Management Science and Operations Research, Information Systems, Computer Networks and Communications and Control and Systems Engineering, having authored 160 papers that have together received 2.2k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (57 papers), Evolutionary Algorithms and Applications (23 papers), Artificial Intelligence in Games (22 papers), Digital Games and Media (12 papers), Multi-Agent Systems and Negotiation (11 papers), Educational Games and Gamification (9 papers), Data Stream Mining Techniques (7 papers) and Metaheuristic Optimization Algorithms Research (7 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Management Science and Operations Research (298 citations), Computer Networks and Communications (416 citations), Computational Theory and Mathematics (253 citations) and Management Information Systems (116 citations). Daniel Kudenko⋆ has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Sam Devlin, Marek Grześ, Kleanthis Malialis, Eduardo Alonso, Dimitar Lubomirov Kazakov, Peter Cowling, G. Flucke, Mark d’Inverno, Jason Noble and Paul A. Cairns. Their work appears in journals such as The Knowledge Engineering Review, Lecture notes in computer science, Neural Computing and Applications, Connection Science and Engineering Applications of 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.