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2021
Towards robust and domain agnostic reinforcement learning competitions.
[DOI]
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
2020
Towards robust and domain agnostic reinforcement learning competitions: MineRL 2020.
[DOI]
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