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Researcher · University of York · United Kingdom

Daniel Kudenko⋆

Daniel Kudenko⋆ publishes mostly in Artificial Intelligence, Computer Networks and Communications and Information Systems, on topics such as Reinforcement Learning in Robotics, Evolutionary Algorithms and Applications and Artificial Intelligence in Games.

ORCID 0000-0003-3359-3255 OpenAlex
World rank
#455,272
of 7,710,434 ranked researchers
Rank in United Kingdom
#39,901
of 367,258
Works
230
Citations
3.3k
Citations per work
14.3
h-index
32
i10-index 77Top 4% in Artificial Intelligence
Daniel Kudenko⋆

What does Daniel Kudenko⋆ research?

Daniel Kudenko⋆'s work is mostly in Computer Science (55%), Engineering (5%), Decision Sciences (5%).

Physical Sciences: 138 works · 60.1% of their workComputer Science: 126 works · 54.9% of their workArtificial Intelligence: 98 works · 42.4% of their workComputer Networks and Communications: 15 works · 6.4% of their workInformation Systems: 14 works · 6.1% of their workEngineering: 12 works · 5.2% of their workControl and Systems Engineering: 12 works · 5.2% of their workEverything else: 71 works · 30.7% of their workSocial Sciences: 21 works · 9.2% of their workDecision Sciences: 12 works · 5.2% of their workManagement Science and Operations Research: 12 works · 5.2% of their workSocial Sciences: 9 works · 4.0% of their workSociology and Political Science: 9 works · 4.0% of their workTHEIR WORKDaniel Kudenko⋆230works
Physical Sciences60%Social Sciences9%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Computer Science12654.9%
    2. Engineering125.2%
  2. Everything else7130.7%
    1. Decision Sciences125.2%
    2. Social Sciences94.0%
  1. 1Artificial Intelligence42% of their works
  2. 2Computer Networks and Communications6% of their works
  3. 3Information Systems6% of their works
  4. 4Management Science and Operations Research5% of their works
  5. 5Control and Systems Engineering5% of their works
  6. 6Sociology and Political Science4% of their works

Research topics

Which keywords describe Daniel Kudenko⋆'s research?

The keywords of their largest research topics: Multi-Agent Systems, Deep Learning, Reinforcement Learning, Evolutionary Algorithms, Genetic Programming, Machine Learning, Monte Carlo Tree Search and Procedural Content Generation.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most.

All 18 words, with their numbers
  1. Multi-Agent Systems952 topics
  2. Deep Learning761 topic
  3. Reinforcement Learning761 topic
  4. Evolutionary Algorithms372 topics
  5. Genetic Programming281 topic
  6. Machine Learning281 topic
  7. Monte Carlo Tree Search261 topic
  8. Procedural Content Generation261 topic
  9. Agent-Based Modeling191 topic
  10. Argumentation Frameworks191 topic
  11. Online Gaming151 topic
  12. Video Games151 topic
  13. Game-Based Learning111 topic
  14. Gamification111 topic
  15. Concept Drift101 topic
  16. Data Streams101 topic
  17. Differential Evolution91 topic
  18. Particle Swarm Optimization91 topic

Where does Daniel Kudenko⋆ work?

Daniel Kudenko⋆'s main affiliation in the publication record is University of York, United Kingdom.

How many publications and citations does Daniel Kudenko⋆ have?

OpenAlex counts 230 works and 3,295 citations for Daniel Kudenko⋆, an h-index of 32, ranking #455,272 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

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