Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback
Published in NeurIPS 2021 Competitions and Demonstrations Track (PMLR), 2022
Recommended citation: Shah, R., Wang, S. H., Wild, C., Milani, S., Kanervisto, A., Goecks, V. G., Waytowich, N., Watkins-Valls, D., Prakash, B., Mills, E., Garg, D., Fries, A., Souly, A., Chan, J. S., del Castillo, D., & Lieberum, T. (2022). Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback. Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, PMLR 176:259-272. https://proceedings.mlr.press/v176/shah22a.html
Abstract
We held the first-ever MineRL Benchmark for Agents that Solve Almost-Lifelike Tasks (MineRL BASALT) Competition at the Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021). The goal of the competition was to promote research towards agents that use learning from human feedback (LfHF) techniques to solve open-world tasks.