Brandon Houghton

According to our database, Brandon Houghton authored at least 13 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, Kai Guan, Yujing Hu, Tangjie Lv, Federico Malato, Florian Leopold, Amogh Raut, Ville Hautamäki, Andrew Melnik, Shu Ishida, João F. Henriques, Robert Klassert, Walter Laurito, Ellen R. Novoseller, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins, Josh Miller, Rohin Shah

CoRR, 2023

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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, Anca D. Dragan

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

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, Helge J. Ritter, Chengjie Wu, Xiaotian Hao, Yiming Lu, Hangyu Mao, Yihuan Mao, Chao Wang, Michal Opanowicz, Anssi Kanervisto, Yanick Schraner, Christian Scheller, Xiren Zhou, Lu Liu, Daichi Nishio, Toi Tsuneda, Karolis Ramanauskas, Gabija Juceviciute

CoRR, 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, Nicholay Topin, Avinash Ummadisingu, Oriol Vinyals

CoRR, 2021

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, Kai Guan, Yujing Hu, Tangjie Lv, Federico Malato, Florian Leopold, Amogh Raut, Ville Hautamäki, Andrew Melnik, Shu Ishida, João F. Henriques, Robert Klassert, Walter Laurito, Lucas Cazzonelli, Cedric Kulbach, Nicholas Popovic, Marvin Schweizer, Ellen R. Novoseller, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins, Josh Miller, Rohin Shah

Proceedings of the NeurIPS 2022 Competition Track, 2021

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 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, Helge J. Ritter, Chengjie Wu, Xiaotian Hao, Yiming Lu, Hangyu Mao, Yihuan Mao, Chao Wang, Michal Opanowicz, Anssi Kanervisto, Yanick Schraner, Christian Scheller, Xiren Zhou, Lu Liu, Daichi Nishio, Toi Tsuneda, Karolis Ramanauskas, Gabija Juceviciute

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020

2019

The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors.

William H. Guss, Cayden 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

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

Proceedings of the NeurIPS 2019 Competition and Demonstration Track, 2019

MineRL: A Large-Scale Dataset of Minecraft Demonstrations.

William H. Guss, Brandon Houghton, Nicholay Topin, Phillip Wang, Cayden Codel, Manuela Veloso, Ruslan Salakhutdinov

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019