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Karl Tuyls

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 54 4593 4464 277 275 335 11138

Karl Tuyls publications per year

The chart shows the history of publications by Karl Tuyls between 1970 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Karl Tuyls published across 56 years, from 1970 to 2025, averaging 6.2 papers a year. Output peaked at 29 publications in 2018. 8 of the 349 publications appeared in the last two years.

No. of publications
5 10 15 20 25
Bar chart. Horizontal axis: year, 1970 to 2025. Vertical axis: number of publications, 0 to 29. Peak 29 publications in 2018. 1970: 1 publication 1971: 0 publications 1972: 0 publications 1973: 0 publications 1974: 0 publications 1975: 0 publications 1976: 0 publications 1977: 0 publications 1978: 0 publications 1979: 0 publications 1980: 0 publications 1981: 0 publications 1982: 0 publications 1983: 0 publications 1984: 0 publications 1985: 0 publications 1986: 0 publications 1987: 0 publications 1988: 0 publications 1989: 0 publications 1990: 0 publications 1991: 0 publications 1992: 0 publications 1993: 0 publications 1994: 0 publications 1995: 0 publications 1996: 0 publications 1997: 0 publications 1998: 0 publications 1999: 0 publications 2000: 0 publications 2001: 3 publications 2002: 5 publications 2003: 4 publications 2004: 4 publications 2005: 17 publications 2006: 17 publications 2007: 13 publications 2008: 23 publications 2009: 19 publications 2010: 6 publications 2011: 14 publications 2012: 20 publications 2013: 26 publications 2014: 22 publications 2015: 22 publications 2016: 12 publications 2017: 11 publications 2018: 29 publications 2019: 17 publications 2020: 12 publications 2021: 25 publications 2022: 14 publications 2023: 5 publications 2024: 4 publications 2025: 4 publications
1970 2025

349 publications in total across all disciplines

View publications per year as a table
Karl Tuyls: publications per year, 1970 to 2025
Year Publications
1970 1
1971 0
1972 0
1973 0
1974 0
1975 0
1976 0
1977 0
1978 0
1979 0
1980 0
1981 0
1982 0
1983 0
1984 0
1985 0
1986 0
1987 0
1988 0
1989 0
1990 0
1991 0
1992 0
1993 0
1994 0
1995 0
1996 0
1997 0
1998 0
1999 0
2000 0
2001 3
2002 5
2003 4
2004 4
2005 17
2006 17
2007 13
2008 23
2009 19
2010 6
2011 14
2012 20
2013 26
2014 22
2015 22
2016 12
2017 11
2018 29
2019 17
2020 12
2021 25
2022 14
2023 5
2024 4
2025 4
Total 349
Download as CSV

Karl Tuyls publications per year - data summary

  • Karl Tuyls, a Computer Science scholar from DeepMind (United Kingdom), has 349 publications recorded across 56 years, from 1970 to 2025.
  • The oldest publication on record dates to 1970 and the most recent to 2025.
  • The most productive year is 2018, with 29 publications.
  • The least productive year with any output is 1970, with 1 publication.
  • 30 of the 56 years in the span carry no publications at all (1971, 1972, 1973, 1974 and others).
  • The rate of publication averages 6.2 papers per year over the whole span, or 13.4 per year counting only the 26 years with at least one publication.
  • The last 5 years on the chart (2021-2025) hold 52 publications, 15% of the career total.
  • Split into equal eras - 1970-1988: 1 publication (0.1 per year); 1989-2007: 63 publications (3.3 per year); 2008-2025: 285 publications (15.8 per year).
  • Comparing the opening and closing eras, the overall trend of publication is rising.

Karl Tuyls publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Karl Tuyls sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 332–341 publications, is where this scientist sits. 32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32–41 publications 991+

This scientist: 335 publications — 80th percentile

80% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209 335
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
Download as CSV

Karl Tuyls publication distribution in Computer Science in 2026 - data summary

  • The chart plots the publication count of all 14,188 Computer Science scientists ranked by Research.com in 2026, grouped into 97 ranges running from 32–41 to 991+ publications.
  • Karl Tuyls, a Computer Science scholar from DeepMind (United Kingdom), records 335 publications - the 80th percentile of the discipline.
  • 80% of ranked Computer Science scientists score the same or lower than Karl Tuyls, and about 20% score higher.
  • The median of the discipline falls in the 202–211 publications range, and Karl Tuyls ranks above the median.
  • The most crowded range is 142–151 publications, holding 609 scientists (4% of the field).
  • 70% of the field sits in the lowest quarter of the value range (up to 272–281 publications), so the distribution is heavily right-skewed and high scores are rare.
  • The final bar has no upper bound: it groups every scientist with 991 publications or more, 100 scientists in all (<1% of the field).

Karl Tuyls D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Karl Tuyls sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 54–55 D-Index, is where this scientist sits. 30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30–31 D-Index 131+

This scientist: 54 D-Index — 69th percentile

69% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500 54
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
Download as CSV

Karl Tuyls D-index placement in Computer Science in 2026 - data summary

  • The chart plots the discipline H-index (D-index) of all 14,188 Computer Science scientists ranked by Research.com in 2026, grouped into 52 ranges running from 30–31 to 131+ D-Index.
  • Karl Tuyls, a Computer Science scholar from DeepMind (United Kingdom), records 54 D-Index - the 69th percentile of the discipline.
  • 69% of ranked Computer Science scientists score the same or lower than Karl Tuyls, and about 31% score higher.
  • The median of the discipline falls in the 44–45 D-Index range, and Karl Tuyls ranks above the median.
  • The most crowded range is 36–37 D-Index, holding 990 scientists (7% of the field).
  • 71% of the field sits in the lowest quarter of the value range (up to 54–55 D-Index), so the distribution is heavily right-skewed and high scores are rare.
  • The final bar has no upper bound: it groups every scientist with 131 D-Index or more, 98 scientists in all (<1% of the field).

Overview

Karl Tuyls is affiliated with DeepMind in the United Kingdom and has contributed extensively to research in computer science and decision sciences. Their work covers a range of topics within artificial intelligence and operations research, with a significant focus on reinforcement learning, game theory, and applications in robotics and sports analytics.

Their main fields of study include:

  • Computer Science
  • Decision Sciences

Tuyls has focused on the following subfields:

  • Artificial Intelligence
  • Management Science and Operations Research
  • Economics and Econometrics
  • Safety Research
  • Sociology and Political Science

Significant topics covered in their research include:

  • Reinforcement Learning in Robotics
  • Advanced Bandit Algorithms Research
  • Game Theory and Applications
  • Artificial Intelligence in Games
  • Sports Analytics and Performance
  • Experimental Behavioral Economics Studies
  • Anomaly Detection Techniques and Applications

They have published numerous research papers, with notable recent contributions such as:

  • Learning a Generic Value-Selection Heuristic Inside a Constraint Programming Solver, 2023, arXiv (Cornell University)
  • Mastering the game of Stratego with model-free multiagent reinforcement learning, 2022, Science
  • From motor control to team play in simulated humanoid football, 2022, Science Robotics
  • TacticAI: an AI assistant for football tactics, 2024, Nature Communications
  • Human-Timescale Adaptation in an Open-Ended Task Space, 2023, arXiv (Cornell University)

Tuyls frequently collaborates with several researchers in their field. Among the most frequent co-authors are:

  • Romuald Élie
  • Daniel Hennes
  • Shayegan Omidshafiei
  • Marc Lanctot
  • Julien Pérolat

Their research has appeared predominantly in venues such as:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Journal of Artificial Intelligence Research
  • Nature Communications
  • Proceedings of the National Academy of Sciences

Best Publications

  • Value-Decomposition Networks For Cooperative Multi-Agent Learning

    Peter Sunehag;Guy Lever;Audrunas Gruslys;Wojciech Marian Czarnecki

  • Multi-Agent Systems

    Unknown

  • Credit Card Fraud Detection Using Bayesian and Neural Networks

    Sam Maes;Karl Tuyls;Bram Vanschoenwinkel;Bernard Manderick

  • Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward

    Peter Sunehag;Guy Lever;Audrunas Gruslys;Wojciech Marian Czarnecki

  • Evolutionary dynamics of multi-agent learning: a survey

    Daan Bloembergen;Karl Tuyls;Daniel Hennes;Michael Kaisers

  • A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning

    Marc Lanctot;Vinícius Flores Zambaldi;Audrunas Gruslys;Angeliki Lazaridou

  • Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment

    K. N. McGuire;C. De Wagter;K. Tuyls;H. J. Kappen

  • Multiagent Learning: Basics, Challenges, and Prospects

    Karl Tuyls;Gerhard Weiss

  • Mastering the game of Stratego with model-free multiagent reinforcement learning

    Unknown

  • Relational Deep Reinforcement Learning.

    Vinícius Flores Zambaldi;David Raposo;Adam Santoro;Victor Bapst

  • Efficient Optical Flow and Stereo Vision for Velocity Estimation and Obstacle Avoidance on an Autonomous Pocket Drone

    Kimberly McGuire;Guido de Croon;Christophe De Wagter;Karl Tuyls

  • The Mechanics of n-Player Differentiable Games

    David Balduzzi;Sébastien Racanière;James Martens;Jakob N. Foerster

  • A selection-mutation model for q-learning in multi-agent systems

    Karl Tuyls;Katja Verbeeck;Tom Lenaerts

  • What evolutionary game theory tells us about multiagent learning

    Karl Tuyls;Simon Parsons

  • Inference of concise DTDs from XML data

    Geert Jan Bex;Frank Neven;Thomas Schwentick;Karl Tuyls

  • Inequity aversion improves cooperation in intertemporal social dilemmas

    Edward Hughes;Joel Z. Leibo;Matthew G. Phillips;Karl Tuyls

  • An Evolutionary Dynamical Analysis of Multi-Agent Learning in Iterated Games

    Karl Tuyls;Pieter Jan Hoen;Bram Vanschoenwinkel

  • Evolutionary game theory and multi-agent reinforcement learning

    Karl Tuyls;Ann Nowé

  • Lenient Multi-Agent Deep Reinforcement Learning

    Gregory Palmer;Karl Tuyls;Daan Bloembergen;Rahul Savani

  • OpenSpiel: A Framework for Reinforcement Learning in Games.

    Marc Lanctot;Edward Lockhart;Jean-Baptiste Lespiau;Vinícius Flores Zambaldi

  • Deep reinforcement learning with relational inductive biases

    Vinícius Flores Zambaldi;David Raposo;Adam Santoro;Victor Bapst

  • Emergent Communication through Negotiation

    Kris Cao;Angeliki Lazaridou;Marc Lanctot;Joel Z. Leibo

  • Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems

    Catholijn M. Jonker;Stacy Marsella;John Thangarajah;Karl Tuyls

  • Introduction to Game Theory

    Karl Tuyls;Ann Nowe

Frequent Co-Authors

Ann Nowé
Ann Nowé Vrije Universiteit Brussel
Marc Lanctot
Marc Lanctot DeepMind (United Kingdom)
Thore Graepel
Thore Graepel University College London
Rémi Munos
Rémi Munos French Institute for Research in Computer Science and Automation - INRIA
Joel Z. Leibo
Joel Z. Leibo DeepMind (United Kingdom)
Simon Parsons
Simon Parsons University of Lincoln
Toon Calders
Toon Calders University of Antwerp
Jan Ramon
Jan Ramon French Institute for Research in Computer Science and Automation - INRIA
Sandip Sen
Sandip Sen University of Tulsa
Wojciech Marian Czarnecki
Wojciech Marian Czarnecki Google

External Links

Personal website of Karl Tuyls Google Scholar page

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Best Scientists Citing Karl Tuyls

Ann Nowé

Ann Nowé

Vrije Universiteit Brussel

Publications: 27

Shimon Whiteson

Shimon Whiteson

University of Oxford

Publications: 22

Jakob Foerster

Jakob Foerster

University of Oxford

Publications: 20

Kagan Tumer

Kagan Tumer

Oregon State University

Publications: 19

Joel Z. Leibo

Joel Z. Leibo

DeepMind (United Kingdom)

Publications: 19

Antonio Liotta

Antonio Liotta

Free University of Bozen-Bolzano

Publications: 18

Marco Baroni

Marco Baroni

Institució Catalana de Recerca i Estudis Avançats

Publications: 16

Thore Graepel

Thore Graepel

University College London

Publications: 15

Vittorio Loreto

Vittorio Loreto

Sapienza University of Rome

Publications: 15

Andrea Baronchelli

Andrea Baronchelli

City, University of London

Publications: 14

Luc Steels

Luc Steels

Spanish National Research Council

Publications: 14

Francisco C. Santos

Francisco C. Santos

Instituto Superior Técnico

Publications: 14

Robert Babuska

Robert Babuska

Delft University of Technology

Publications: 14

Sandip Sen

Sandip Sen

University of Tulsa

Publications: 13

Marc Lanctot

Marc Lanctot

DeepMind (United Kingdom)

Publications: 13

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Ana L. C. Bazzan

Federal University of Rio Grande do Sul

Publications: 13

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2027 How to Become a Special Education Teacher in Houston, TX: Education Requirements & Certification
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2027 Entertainment Business Degree Programs That Accept Transfer Credits
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2027 Most Affordable Online Public Administration Degrees