To facilitate research in the direction of fine-tuning foundation models from human feedback, we held the MineRL BASALT Competition on Fine-Tuning from Human Feedback at NeurIPS 2022. The BASALT challenge asks teams to compete to develop algorithms to solve tasks with hard-to-specify reward functions in Minecraft. Through this competition, we aimed to promote the development of algorithms that use human feedback as channels to learn the desired behavior. We describe the competition and provide an overview of the top solutions. We conclude by discussing the impact of the competition and future directions for improvement.

翻译：为促进基于人类反馈的预训练模型微调研究方向，我们在NeurIPS 2022上举办了MineRL BASALT人类反馈微调竞赛。BASALT挑战赛要求参赛团队开发算法，解决Minecraft中难以明确指定奖励函数的任务。通过此项竞赛，我们旨在推动利用人类反馈作为学习期望行为通道的算法发展。本文阐述了竞赛详情，概述了优胜方案，并最终讨论了竞赛的影响及未来改进方向。