PeopleofSuperintelligence

Researcher

Marc Lanctot

Marc Lanctot is a research scientist whose work connects reinforcement learning, game theory and search in games. He studied computer science and games at McGill and earned a PhD in artificial intelligence at Alberta. He coauthored work on Monte Carlo counterfactual regret minimization, OpenSpiel and Student of Games. His 2016 paper on dueling networks won the ICML Best Paper Award, and a 2025 paper on ranking general agents won the AAMAS Best Paper Award. As of October 2026, he is a research scientist interested in multiagent reinforcement learning, game theory, games and search/planning.

Works
146
Citations
29,252
h-index
35
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2005

    An MSc at McGill

    At McGill's School of Computer Science and Games Research, he studies under Clark Verbrugge. His MSc thesis, Adaptive Virtual Environments in Multi-player Computer Games, appears in 2005.

  2. 2009

    Monte Carlo regret sampling

    In 2009, he coauthors Monte Carlo Sampling for Regret Minimization in Extensive Games with Kevin Waugh, Martin Zinkevich and Michael Bowling. The paper introduces MCCFR, a family of sample-based methods that compute approximate equilibria through self-play.

  3. 2013

    An artificial intelligence PhD

    In 2013, he earns a PhD in artificial intelligence from the University of Alberta's Department of Computer Science.

  4. 2016

    Dueling networks at DeepMind

    Before joining DeepMind, he completes a postdoctoral research fellowship at Maastricht University's Department of Knowledge Engineering. In 2016, he coauthors Dueling Network Architectures for Deep Reinforcement Learning with Google DeepMind researchers; its separate state-value and action-advantage estimates help improve policy evaluation. The paper wins ICML's Best Paper Award.

  5. 2019–2026

    OpenSpiel for game research

    In 2019, he coauthors OpenSpiel, a collection of environments and algorithms for general reinforcement learning and search/planning in games. In July 2026, he announces OpenSpiel 2.0 with John Schultz, Daniel Hennes and Zun Li; the release adds 19 games and an AlphaZero port to JAX.

  6. 2023

    Student of Games

    In 2023, he coauthors Student of Games, a general-purpose algorithm that combines guided search, self-play learning and game-theoretic reasoning.

  7. 2025

    Ranking general agents

    In 2025, he coauthors Soft Condorcet Optimization for Ranking of General Agents, a social-choice method for ranking AI agents. The paper wins the AAMAS Best Paper Award.

  8. As of October 2026

    Research scientist after DeepMind

    In September 2026, he announces that he no longer works at Google DeepMind. As of October 2026, he is a research scientist interested in multiagent reinforcement learning, game theory, games and search/planning.

Career

  1. 2020–2022University of Alberta
  2. 2015–2026Google DeepMind
  3. 2015–2026Google
  4. 2013–2016Maastricht UniversityPostdoctoral Research Fellow

Education

  1. 2013University of AlbertaPhD
  2. 2005McGill UniversityMSc

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. Mastering the game of Go with deep neural networks and tree search2016 · Nature · 15,585 citationsWith Aja Huang, Arthur Guez, Chris J. Maddison, David Silver, Demis Hassabis and George van den Driessche
  2. A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play2018 · Science · 3,555 citationsWith Arthur Guez, David Silver, Demis Hassabis, Ioannis Antonoglou, Julian Schrittwieser and Karen Simonyan
  3. Dueling Network Architectures for Deep Reinforcement Learning2015 · 3,300 citationsWith Hado van Hasselt, Nando de Freitas and Tom Schaul
  4. Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm2017 · 1,053 citationsWith Arthur Guez, David Silver, Demis Hassabis, Ioannis Antonoglou, Julian Schrittwieser and Karen Simonyan
  5. Deep Q-learning From Demonstrations2018 · Proceedings of the AAAI Conference on Artificial Intelligence · 885 citationsWith Tom Schaul

From OpenAlex, as of 21 October 2026.

  1. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Marc Lanctot. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  2. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Marc Lanctot. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  3. Google had the most people shaping AI every year from 2014 to 2025Includes Google. Our estimates of which organizations employed the most people shaping AI each year from 1955 to 2025, tracing the shift from university labs to companies.
  4. Google has the highest combined h-index among AI organizationsIncludes Google. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Marc Lanctot yet. Send us a free-licensed photo.

  1. Marc Lanctot's Web Site mlanctot.info. Checked 21 October 2026.
  2. Monte Carlo Sampling for Regret Minimization in Extensive Games proceedings.neurips.cc. Checked 21 October 2026.
  3. University of Maryland MARL - Dr. Marc Lanctot, Google DeepMind, November 17, 2022 sites.google.com. Checked 21 October 2026.
  4. Awards | ICML New York City icml.cc. Checked 21 October 2026.
  5. OpenSpiel: A Framework for Reinforcement Learning in Games arxiv.org. Checked 21 October 2026.
  6. Introducing OpenSpiel 2.0 mlanctot.info. Checked 21 October 2026.
  7. Student of Games: A unified learning algorithm for both perfect and imperfect information games pmc.ncbi.nlm.nih.gov. Checked 21 October 2026.
  8. Soft Condorcet Optimization for Ranking of General Agents arxiv.org. Checked 21 October 2026.
  9. Ranking AI: Professor Kate Larson wins Paper Award at AAMAS cs.uwaterloo.ca. Checked 21 October 2026.
  10. Admin change · Issue #1621 · google-deepmind/open_spiel github.com. Checked 21 October 2026.