Daniel Kudenko⋆

3.2k citations
116 papers · 1.5k indexed · h-index 21

Impact in

Papers in

Daniel Kudenko⋆

110 papers receiving 1.4k citations

Peers

Daniel Kudenko⋆
Comparison fields: 5 of 117
  • Artificial Intelligence 883
  • Management Science and Operations Research 197
  • Management Information Systems 104
  • Computer Networks and Communications 264
  • Computational Theory and Mathematics 163
Replace Dave Cliff with:
Dave Cliff United Kingdom
Mehdi Dastani Netherlands
Juan A. Rodríguez-Aguilar Spain
Lin Padgham Australia
Matteo Gaeta Italy
Sam Devlin United Kingdom
David V. Pynadath United States
Mark d’Inverno United Kingdom
Gillian Dobbie New Zealand
Neil Yorke‐Smith Netherlands
Daniel Kudenko⋆ relative to Dave Cliff United Kingdom Dave Cliff's profile →
Citations per field
00.5×4.7×
Dave Cliff · 1×
Citations per year

Countries citing papers authored by Daniel Kudenko⋆

Since Specialization
Citations

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⋆

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Daniel Kudenko⋆ Line = papers co-authored together Daniel Kudenko⋆ links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 116 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002116
2 201787
3 200184
4 201275
5 201555
6 200849
7 201149
8 201148
9 201548
10 201443
11 201041
12 201440
13 200733
14 201929
15 200428
16 200527
17 201525
18
Feature generation for sequence categorization
199823
19
Combining Ethnographic and Clickstream Data to Identify User Web Browsing Strategies
200622
20 200322

About Daniel Kudenko⋆

Daniel Kudenko⋆ is a scholar working on Artificial Intelligence, Management Science and Operations Research, Information Systems, Computer Networks and Communications and Computational Theory and Mathematics, having authored 116 papers that have together received 1.5k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (42 papers), Artificial Intelligence in Games (15 papers), Evolutionary Algorithms and Applications (12 papers), Digital Games and Media (9 papers), Multi-Agent Systems and Negotiation (9 papers), Semantic Web and Ontologies (6 papers), Simulation Techniques and Applications (6 papers) and Educational Games and Gamification (6 papers). The work is most often cited by research in Artificial Intelligence (883 citations), Management Science and Operations Research (197 citations), Management Information Systems (104 citations), Computer Networks and Communications (264 citations) and Computational Theory and Mathematics (163 citations). Daniel Kudenko⋆ has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Sam Devlin, Marek Grześ, Peter Cowling, Eduardo Alonso, Chris Kimble, Mark d’Inverno, Jason Noble, G. Flucke, I‐Hsien Ting and Ignazio Cabras. Their work appears in journals such as The Knowledge Engineering Review, Neural Computing and Applications, Connection Science, Ecological Indicators and Autonomous Agents and Multi-Agent Systems.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026