Marc Lanctot

26.9k citations
47 papers · 13.6k · 4 hit papers · h-index 20

Impact in

    • Reinforcement Learning in Robotics
    • Artificial Intelligence in Games
    • Evolutionary Algorithms and Applications
    • Adversarial Robustness in Machine Learning

Papers in

Marc Lanctot

42 papers receiving 13.0k citations

Marc Lanctot's Hit Papers

Deep Q-learning From Demonstrations 2018 · 493 citations
4930+3+7Years since publication2.5k5.0k7.5k

Peers

Marc Lanctot
Comparison fields: 5 of 202
  • Artificial Intelligence 7.5k
  • Health Informatics 137
  • Computer Vision and Pattern Recognition 2.0k
  • Management Science and Operations Research 992
  • Automotive Engineering 907
Replace George van den Driessche with:
George van den Driessche United Kingdom
Aja Huang United Kingdom
Julian Schrittwieser United Kingdom
Nal Kalchbrenner United States
Laurent Sifre United Kingdom
Thore Graepel United Kingdom
Sander Dieleman Belgium
Dominik Grewe United Kingdom
Chris J. Maddison Canada
Stig Petersen United Kingdom
Marc Lanctot relative to George van den Driessche United Kingdom George van den Driessche's profile →
Citations per field
00.5×1.5×
George van den Driessche · 1×
Citations per year

Countries citing papers authored by Marc Lanctot

Since Specialization
Citations

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

Fields of papers citing papers by Marc Lanctot

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Mastering the game of Go with deep neural networks and tree search
Hit paper breakdown →
20168961
2
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
Hit paper breakdown →
20181882
3
Dueling Network Architectures for Deep Reinforcement Learning
Hit paper breakdown →
20151040
4
Deep Q-learning From Demonstrations
Hit paper breakdown →
2018493
5 2018240
6 2017124
7 2019104
8 200998
9
Fictitious Self-Play in Extensive-Form Games
201568
10 201759
11 200745
12
Learning from Demonstrations for Real World Reinforcement Learning
201744
13 201644
14 201439
15 201829
16 201229
17 201928
18 201224
19 201423
20 201621

About Marc Lanctot

Marc Lanctot is a scholar working on Artificial Intelligence, Economics and Econometrics, Management Science and Operations Research, Sociology and Political Science and Safety Research, having authored 47 papers that have together received 13.6k indexed citations. Recurring topics across this work include Artificial Intelligence in Games (27 papers), Reinforcement Learning in Robotics (22 papers), Sports Analytics and Performance (18 papers), Advanced Bandit Algorithms Research (9 papers), Game Theory and Applications (8 papers), Digital Games and Media (6 papers), Experimental Behavioral Economics Studies (5 papers) and Gambling Behavior and Treatments (4 papers). The work is most often cited by research in Artificial Intelligence (7.5k citations), Health Informatics (137 citations), Computer Vision and Pattern Recognition (2.0k citations), Management Science and Operations Research (992 citations) and Automotive Engineering (907 citations). Marc Lanctot has collaborated with scholars based in United Kingdom, Canada and United States. Frequent co-authors include Thore Graepel, David Silver, Timothy Lillicrap, Laurent Sifre, Arthur Guez, Julian Schrittwieser, Ioannis Antonoglou, Demis Hassabis, Dominik Grewe and George van den Driessche. Their work appears in journals such as Artificial Intelligence, Scientific Reports, Science, Autonomous Agents and Multi-Agent Systems 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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