🧑‍🔬 Marc G. Bellemare

🏛️ Affiliations

🏢GoogleMountain View · United States2016–2024 · 41 papersEmployment🏢Google DeepMindLondon · United Kingdom2014–2022 · 13 papers🎓McGill UniversityMontreal · Canada2007–2025 · 10 papers🎓University of AlbertaEdmonton · Canada2011–2021 · 6 papersEducation🔬Mila - Quebec Artificial Intelligence InstituteMontreal · Canada2019–2024 · 4 papers🎓Université de MontréalMontreal · Canada2019–2023 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

2010s

📄 Papers

The most cited first (OpenAlex and our library).

1. The Arcade Learning Environment: An Evaluation Platform for General Agents (2012 · 1,257 citations)
   The paper tackles the problem of fairly assessing AI agents meant to be broadly competent rather than tuned to a single task.
2. Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (2017 · 393 citations)
   The Arcade Learning Environment (ALE) is a popular testbed for general AI agents that must play many Atari 2600 games without game-specific knowledge.
3. Deep Reinforcement Learning at the Edge of the Statistical Precipice (2021 · 90 citations)
   The authors examine how reliably algorithms are compared in deep RL when only a few runs per task are available.

All works

7 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. The Arcade Learning Environment: An Evaluation Platform for General AgentsJournal of Artificial Intelligence ResearchMarc G. Bellemare, Yavar Naddaf, Joel Veness, et al.2012 · 1,257 citations
2. Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General AgentsJournal of Artificial Intelligence ResearchMarlos C. Machado, Marc G. Bellemare, Erik Talvitie, et al.2017 · 393 citations
3. Unifying Count-Based Exploration and Intrinsic Motivation ↗arXiv:1606.01868 · no summary yetMarc G. Bellemare et al.2016 · 311 citations
4. Autonomous navigation of stratospheric balloons using reinforcement learning ↗Nature · no summary yetMarc G. Bellemare et al.2020 · 296 citations
5. Automated Curriculum Learning for Neural Networks ↗arXiv:1704.03003 · no summary yetAlex Graves et al.2017 · 111 citations
6. Deep Reinforcement Learning at the Edge of the Statistical PrecipicearXiv:2108.13264Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, et al.2021 · 90 citations
7. Investigating Contingency Awareness Using Atari 2600 Games ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetMarc G. Bellemare, Joel Veness, Michael Bowling75 citations

🤝 Co-authors here

5 co-authors with a page, the most papers together first.

• Joel Veness ×2
• Michael Bowling ×2
• Aaron Courville
• Matthew Hausknecht
• Rishabh Agarwal

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Journal of Artificial Intelligence Research ×2: Journal of Artificial Intelligence Research 2017, Journal of Artificial Intelligence Research 2012
• Nature
• Proceedings of the AAAI Conference on Artificial Intelligence

🔗 Cited by

Papers of our library cite their works 405 times (of the 149,439 papers whose bibliographies we read); 38 citing papers with a page here →.

Updated 2 November 2026

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