Kevin Waugh

2.1k citations
58 papers · 1.1k · 1 hit paper · h-index 15

Impact in

    • Artificial Intelligence in Games
    • Reinforcement Learning in Robotics
  • Software top 5%
    • Model-Driven Software Engineering Techniques

Papers in

Kevin Waugh

58 papers receiving 1.0k citations

Kevin Waugh's Hit Papers

DeepStack: Expert-level artificial intelligence in heads-up no-limit poker 2017 · 424 citations
4240+3+6Years since publication100200300400

Peers

Kevin Waugh
Comparison fields: 5 of 107
  • Artificial Intelligence 737
  • Software 85
  • Health Informatics 27
  • Management Science and Operations Research 225
  • Computer Science Applications 86
Replace Amos Azaria with:
Amos Azaria Israel
Judy Goldsmith United States
John‐Jules Ch. Meyer Netherlands
Linyi Yang China
Wei Ye China
Liz Sonenberg Australia
Rajni Jindal India
Jimmy H. M. Lee Hong Kong
Varol Akman Türkiye
Kevin Waugh relative to Amos Azaria Israel Amos Azaria's profile →
Citations per field
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Citations per year

Countries citing papers authored by Kevin Waugh

Since Specialization
Citations

This map shows the geographic impact of Kevin Waugh'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 Kevin Waugh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Waugh more than expected).

Fields of papers citing papers by Kevin Waugh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin Waugh. 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 Kevin Waugh. The network helps show where Kevin Waugh may publish in the future.

Co-authors

The 25 scholars most cited alongside Kevin Waugh, 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 Kevin Waugh Line = papers co-authored together Kevin Waugh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1
DeepStack: Expert-level artificial intelligence in heads-up no-limit poker
Hit paper breakdown →
2017424
2 200998
3 200949
4 200946
5 201145
6
A Practical Use of Imperfect Recall
200938
7 200732
8 202331
9 200729
10 200527
11 200820
12 200617
13 200717
14 201216
15
A PATTERN CATALOG FOR COMPUTER ROLE PLAYING GAMES
200515
16 200614
17 201513
18
Strategy Grafting in Extensive Games
200912
19 201512
20 199211

About Kevin Waugh

Kevin Waugh is a scholar working on Artificial Intelligence, Information Systems, Software, Computer Vision and Pattern Recognition and Sociology and Political Science, having authored 58 papers that have together received 1.1k indexed citations. Recurring topics across this work include Artificial Intelligence in Games (23 papers), Model-Driven Software Engineering Techniques (16 papers), Software Engineering Research (10 papers), Data Visualization and Analytics (9 papers), Digital Games and Media (9 papers), Sports Analytics and Performance (8 papers), Semantic Web and Ontologies (8 papers) and Gambling Behavior and Treatments (6 papers). The work is most often cited by research in Artificial Intelligence (737 citations), Software (85 citations), Health Informatics (27 citations), Management Science and Operations Research (225 citations) and Computer Science Applications (86 citations). Kevin Waugh has collaborated with scholars based in United Kingdom, Canada and United States. Frequent co-authors include Michael Bowling, Michael Johanson, Peter Thomas, Neil Smith, Dustin Morrill, Nolan Bard, Martin Schmid, Trevor Davis, Neil Burch and Matej Moravčík. Their work appears in journals such as Computer, Learning Media and Technology, Science, Mathematical Programming and Science Advances.

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.

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