Marc Lanctot
Impact in
- Artificial Intelligence top 0.05%
- Reinforcement Learning in Robotics
- Artificial Intelligence in Games
- Evolutionary Algorithms and Applications
- Adversarial Robustness in Machine Learning
- Health Informatics top 1%
Papers in
-
- Artificial Intelligence in Games 26
- Reinforcement Learning in Robotics 21
- Co-authors
- Thore GraepelDavid SilverJulian SchrittwieserArthur GuezIoannis AntonoglouDemis HassabisTimothy LillicrapLaurent Sifre
- Journals
- Artificial Intelligence (3 papers)Scientific Reports (1 paper)Nature (1 paper)Science Advances (1 paper)IEEE Transactions on Computational Intelligence and AI in Games (1 paper)
- Partner nations
- United KingdomCanadaUnited States
In The Last Decade
Marc Lanctot
40 papers receiving 12.6k citations
Hit Papers
Peers
Comparison fields: 5 of 202
- Artificial Intelligence 7.4k
- Health Informatics 145
- Computer Vision and Pattern Recognition 2.0k
- Management Science and Operations Research 957
- Automotive Engineering 903
Countries citing papers authored by Marc Lanctot
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
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-authorship network
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.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2020 | 16 | |
| 3 | Fast computation of Nash Equilibria in Imperfect Information Games | 2020 | 1 |
| 4 | 2020 | 8 | |
| 5 | 2019 | 100 | |
| 6 | 2018 | 229 | |
| 7 | A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play Hit paper breakdown → | 2018 | 1827 |
| 8 | 2018 | 29 | |
| 9 | Learning from Demonstrations for Real World Reinforcement Learning | 2017 | 43 |
| 10 | 2017 | 59 | |
| 11 | 2016 | 21 | |
| 12 | Mastering the game of Go with deep neural networks and tree search Hit paper breakdown → | 2016 | 8793 |
| 13 | 2014 | 22 | |
| 14 | 2013 | 4 | |
| 15 | An Introduction to Counterfactual Regret Minimization | 2013 | 10 |
| 16 | 2012 | 23 | |
| 17 | Efficient Monte Carlo Counterfactual Regret Minimization in Games with Many Player Actions | 2012 | 11 |
| 18 | Variance Reduction in Monte-Carlo Tree Search | 2011 | 8 |
| 19 | MCRNR: fast computing of restricted Nash responses by means of sampling | 2010 | 3 |
| 20 | Locally-Adaptive Virtual Environments in Persistent-state Multi-player Games | 2004 | 1 |
About Marc Lanctot
Marc Lanctot is a scholar working on General Decision Sciences, Artificial Intelligence, Management Science and Operations Research, Economics and Econometrics and Safety Research, having authored 45 papers that have together received 13.3k indexed citations. Recurring topics across this work include Artificial Intelligence in Games (26 papers), Reinforcement Learning in Robotics (21 papers), Sports Analytics and Performance (17 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 (7.4k citations), Health Informatics (145 citations), Computer Vision and Pattern Recognition (2.0k citations), Management Science and Operations Research (957 citations) and Automotive Engineering (903 citations). Marc Lanctot has collaborated with scholars based in United Kingdom, Canada and United States. Frequent co-authors include Thore Graepel, David Silver, Julian Schrittwieser, Arthur Guez, Ioannis Antonoglou, Demis Hassabis, Timothy Lillicrap, Laurent Sifre, Aja Huang and Nal Kalchbrenner. Their work appears in journals such as Artificial Intelligence, Scientific Reports, Nature, Science Advances and IEEE Transactions on Computational Intelligence and AI in Games.
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.