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Olivier Sigaud

Olivier Sigaud

Sorbonne University
France

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 34 12235 11878 309 299 207 4511

Olivier Sigaud publications per year

The chart shows the history of publications by Olivier Sigaud between 1996 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Olivier Sigaud published across 30 years, from 1996 to 2025, averaging 7.7 papers a year. Output peaked at 21 publications in 2020. 8 of the 230 publications appeared in the last two years.

No. of publications
5 10 15 20
Bar chart. Horizontal axis: year, 1996 to 2025. Vertical axis: number of publications, 0 to 21. Peak 21 publications in 2020. 1996: 1 publication 1997: 0 publications 1998: 0 publications 1999: 1 publication 2000: 3 publications 2001: 5 publications 2002: 6 publications 2003: 7 publications 2004: 6 publications 2005: 3 publications 2006: 7 publications 2007: 7 publications 2008: 5 publications 2009: 8 publications 2010: 8 publications 2011: 6 publications 2012: 18 publications 2013: 15 publications 2014: 12 publications 2015: 6 publications 2016: 5 publications 2017: 4 publications 2018: 20 publications 2019: 12 publications 2020: 21 publications 2021: 12 publications 2022: 16 publications 2023: 8 publications 2024: 4 publications 2025: 4 publications
1996 2025

230 publications in total across all disciplines

View publications per year as a table
Olivier Sigaud: publications per year, 1996 to 2025
Year Publications
1996 1
1997 0
1998 0
1999 1
2000 3
2001 5
2002 6
2003 7
2004 6
2005 3
2006 7
2007 7
2008 5
2009 8
2010 8
2011 6
2012 18
2013 15
2014 12
2015 6
2016 5
2017 4
2018 20
2019 12
2020 21
2021 12
2022 16
2023 8
2024 4
2025 4
Total 230
Download as CSV

Olivier Sigaud 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 Olivier Sigaud 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, 202–211 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: 207 publications — 49th percentile

49% 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
202–211 508 207
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
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

Olivier Sigaud 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 Olivier Sigaud 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, 34–35 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: 34 D-Index — 16th percentile

16% 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 34
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
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

Overview

Olivier Sigaud is affiliated with Sorbonne University in France and has a research focus primarily within the field of Computer Science, contributing notably to Artificial Intelligence and its subfields. Their work spans across several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Biomedical Engineering, and Mechanical Engineering.

The scientist's main topics of research cover diverse areas such as Reinforcement Learning in Robotics, Robot Manipulation and Learning, Natural Language Processing Techniques, Evolutionary Algorithms and Applications, Modular Robots and Swarm Intelligence, Domain Adaptation and Few-Shot Learning, and Robotic Path Planning Algorithms.

Olivier Sigaud has published extensively, with a substantial number of contributions appearing in venues such as:

  • arXiv (Cornell University)
  • Communications Biology
  • HAL (Le Centre pour la Communication Scientifique Directe)
  • Journal of Artificial Intelligence Research
  • ACM Transactions on Evolutionary Learning and Optimization

Recent research papers authored or co-authored by Olivier Sigaud include:

  • "Combining Evolution and Deep Reinforcement Learning for Policy Search: A Survey," 2022, ACM Transactions on Evolutionary Learning and Optimization
  • "Autotelic Agents with Intrinsically Motivated Goal-Conditioned Reinforcement Learning: A Short Survey," 2022, Journal of Artificial Intelligence Research
  • "Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning," 2023, arXiv (Cornell University)
  • "Interactively shaping robot behaviour with unlabeled human instructions," 2020, Autonomous Agents and Multi-Agent Systems
  • "Grounding Language to Autonomously-Acquired Skills via Goal Generation," 2020, arXiv (Cornell University)

The scientist collaborates regularly with several frequent co-authors, including:

  • Mohamed Chétouani
  • Cédric Colas
  • Pierre-Yves Oudeyer
  • Nicolas Perrin-Gilbert
  • Ahmed Akakzia

Best Publications

  • Many regression algorithms, one unified model

    Freek Stulp;Olivier Sigaud

  • Path Integral Policy Improvement with Covariance Matrix Adaptation

    Freek Stulp;Freek Stulp;Olivier Sigaud

  • On-line regression algorithms for learning mechanical models of robots: A survey

    Olivier Sigaud;Camille Salaün;Vincent Padois

  • Robot Skill Learning: From Reinforcement Learning to Evolution Strategies

    Freek Stulp;Olivier Sigaud

  • Learning the structure of Factored Markov Decision Processes in reinforcement learning problems

    Thomas Degris;Olivier Sigaud;Pierre-Henri Wuillemin

  • Anticipatory Behavior in Adaptive Learning Systems

    Giovanni Pezzulo;Martin V. Butz;Olivier Sigaud;Gianluca Baldassarre

  • Learning classifier systems: a survey

    Olivier Sigaud;Stewart W. Wilson

  • Reinforcement Learning

    Unknown

  • Anticipatory Behavior in Adaptive Learning Systems: Foundations, Theories, and Systems

    Martin V. Butz;Olivier Sigaud;Pierre Gérard

  • Anticipatory Behavior: Exploiting Knowledge About the Future to Improve Current Behavior

    Martin V. Butz;Martin V. Butz;Olivier Sigaud;Pierre Gérard

  • Internal Models and Anticipations in Adaptive Learning Systems

    Martin V. Butz;Martin V. Butz;Olivier Sigaud;Pierre Gérard

  • CEM-RL: Combining evolutionary and gradient-based methods for policy search.

    Aloïs Pourchot;Olivier Sigaud

  • CEM-RL: Combining evolutionary and gradient-based methods for policy search

    Aloïs Pourchot;Olivier Sigaud

  • GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms

    Cédric Colas;Olivier Sigaud;Pierre-Yves Oudeyer

  • Markov Decision Processes in Artificial Intelligence

    Olivier Sigaud;Olivier Buffet

  • Autotelic Agents with Intrinsically Motivated Goal-Conditioned Reinforcement Learning: A Short Survey

    Unknown

  • Modelling Individual Differences in the Form of Pavlovian Conditioned Approach Responses: A Dual Learning Systems Approach with Factored Representations

    Florian Lesaint;Olivier Sigaud;Shelly B. Flagel;Shelly B. Flagel;Terry E. Robinson

  • From Motor Learning to Interaction Learning in Robots

    Olivier Sigaud;Jan Peters

  • Object Learning Through Active Exploration

    Serena Ivaldi;Sao Mai Nguyen;Natalia Lyubova;Alain Droniou

  • Learning compact parameterized skills with a single regression

    Freek Stulp;Gennaro Raiola;Antoine Hoarau;Serena Ivaldi

  • Policy Improvement Methods: Between Black-Box Optimization and Episodic Reinforcement Learning

    Freek Stulp;Olivier Sigaud

  • Policy search in continuous action domains: An overview.

    Olivier Sigaud;Freek Stulp

  • How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments

    Cédric Colas;Olivier Sigaud;Pierre-Yves Oudeyer

  • GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms

    Cédric Colas;Olivier Sigaud;Pierre-Yves Oudeyer

  • CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement Learning

    Cédric Colas;Pierre Fournier;Olivier Sigaud;Mohamed Chetouani

Frequent Co-Authors

Mohamed Chetouani
Mohamed Chetouani Sorbonne University
Pierre-Yves Oudeyer
Pierre-Yves Oudeyer French Institute for Research in Computer Science and Automation - INRIA
Freek Stulp
Freek Stulp German Aerospace Center
Martin V. Butz
Martin V. Butz University of Tübingen
Giovanni Pezzulo
Giovanni Pezzulo National Academies of Sciences, Engineering, and Medicine
Gianluca Baldassarre
Gianluca Baldassarre National Academies of Sciences, Engineering, and Medicine
Timothy M. Hospedales
Timothy M. Hospedales University of Edinburgh
Nando de Freitas
Nando de Freitas DeepMind (United Kingdom)
Francesco Nori
Francesco Nori DeepMind (United Kingdom)
Shelly B. Flagel
Shelly B. Flagel University of Michigan–Ann Arbor

External Links

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Best Scientists Citing Olivier Sigaud

Martin V. Butz

Martin V. Butz

University of Tübingen

Publications: 51

Pierre-Yves Oudeyer

Pierre-Yves Oudeyer

French Institute for Research in Computer Science and Automation - INRIA

Publications: 46

Jan Peters

Jan Peters

Technical University of Darmstadt

Publications: 31

Sylvain Calinon

Sylvain Calinon

Idiap Research Institute

Publications: 30

Sergey Levine

Sergey Levine

University of California, Berkeley

Publications: 24

Freek Stulp

Freek Stulp

German Aerospace Center

Publications: 21

Mohamed Chetouani

Mohamed Chetouani

Sorbonne University

Publications: 19

Jean-Baptiste Mouret

Jean-Baptiste Mouret

University of Lorraine

Publications: 15

Ales Ude

Ales Ude

Jožef Stefan Institute

Publications: 14

Stefan Wermter

Stefan Wermter

Universität Hamburg

Publications: 13

Gianluca Baldassarre

Gianluca Baldassarre

National Academies of Sciences, Engineering, and Medicine

Publications: 13

Darwin G. Caldwell

Darwin G. Caldwell

Italian Institute of Technology

Publications: 13

Giulio Sandini

Giulio Sandini

Italian Institute of Technology

Publications: 12

Peter Stone

Peter Stone

The University of Texas at Austin

Publications: 12

Gerhard Neumann

Gerhard Neumann

Karlsruhe Institute of Technology

Publications: 11

Jochen J. Steil

Jochen J. Steil

Technische Universität Braunschweig

Publications: 11

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