MineRL: A Large-Scale Dataset of Minecraft Demonstrations. - William H. Guss; Brandon Houghton; Nicholay Topin; Phillip Wang; Cayden R. Codel; Manuela Veloso; Ruslan Salakhutdinov (IJCAI, 2019)

Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning. - Stephanie Milani; Nicholay Topin; Brandon Houghton; William H. Guss; Sharada P. Mohanty; Keisuke Nakata; Oriol Vinyals; Noboru Sean Kuno (NeurIPS (Competition and Demos), 2019)

The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors. - William H. Guss; Cayden R. Codel; Katja Hofmann; Brandon Houghton; Noburu Kuno; Stephanie Milani; Sharada P. Mohanty; Diego Perez Liebana; Ruslan Salakhutdinov; Nicholay Topin; Manuela Veloso; Phillip Wang (CoRR, 2019)

Towards robust and domain agnostic reinforcement learning competitions: MineRL 2020. - William Hebgen Guss; Stephanie Milani; Nicholay Topin; Brandon Houghton; Sharada P. Mohanty; Andrew Melnik; Augustin Harter; Benoit Buschmaas; Bjarne Jaster; Christoph Berganski; Dennis Heitkamp; Marko Henning; et al. (NeurIPS (Competition and Demos), 2020)

Guaranteeing Reproducibility in Deep Learning Competitions. - Brandon Houghton; Stephanie Milani; Nicholay Topin; William H. Guss; Katja Hofmann; Diego Perez Liebana; Manuela Veloso; Ruslan Salakhutdinov (CoRR, 2020)

Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition. - Stephanie Milani; Anssi Kanervisto; Karolis Ramanauskas; Sander Schulhoff; Brandon Houghton; Sharada P. Mohanty; Byron Galbraith; Ke Chen; Yan Song; Tianze Zhou; Bingquan Yu; He Liu; et al. (NeurIPS (Competition and Demos), 2021)

The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors. - William H. Guss; Mario Ynocente Castro; Sam Devlin; Brandon Houghton; Noboru Sean Kuno; Crissman Loomis; Stephanie Milani; Sharada P. Mohanty; Keisuke Nakata; Ruslan Salakhutdinov; John Schulman; Shinya Shiroshita; et al. (CoRR, 2021)

Towards robust and domain agnostic reinforcement learning competitions. - William Hebgen Guss; Stephanie Milani; Nicholay Topin; Brandon Houghton; Sharada P. Mohanty; Andrew Melnik; Augustin Harter; Benoit Buschmaas; Bjarne Jaster; Christoph Berganski; Dennis Heitkamp; Marko Henning; et al. (CoRR, 2021)

Multi-task curriculum learning in a complex, visual, hard-exploration domain: Minecraft. - Ingmar Kanitscheider; Joost Huizinga; David Farhi; William Hebgen Guss; Brandon Houghton; Raul Sampedro; Peter Zhokhov; Bowen Baker; Adrien Ecoffet; Jie Tang; Oleg Klimov; Jeff Clune (CoRR, 2021)

The MineRL BASALT Competition on Learning from Human Feedback. - Rohin Shah; Cody Wild; Steven H. Wang; Neel Alex; Brandon Houghton; William H. Guss; Sharada P. Mohanty; Anssi Kanervisto; Stephanie Milani; Nicholay Topin; Pieter Abbeel; Stuart Russell 001; et al. (CoRR, 2021)

Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos. - Bowen Baker; Ilge Akkaya; Peter Zhokhov; Joost Huizinga; Jie Tang; Adrien Ecoffet; Brandon Houghton; Raul Sampedro; Jeff Clune (NeurIPS, 2022)

BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents that Solve Fuzzy Tasks. - Stephanie Milani; Anssi Kanervisto; Karolis Ramanauskas; Sander Schulhoff; Brandon Houghton; Rohin Shah (NeurIPS, 2023)

Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition. - Stephanie Milani; Anssi Kanervisto; Karolis Ramanauskas; Sander Schulhoff; Brandon Houghton; Sharada P. Mohanty; Byron Galbraith; Ke Chen; Yan Song; Tianze Zhou; Bingquan Yu; He Liu; et al. (CoRR, 2023)

OpenAI o1 System Card. - Aaron Jaech; Adam Kalai; Adam Lerer; Adam Richardson; Ahmed El-Kishky; Aiden Low; Alec Helyar; Aleksander Madry; Alex Beutel; Alex Carney; Alex Iftimie; Alex Karpenko; et al. (CoRR, 2024)