论文标题
Minecraft中的缩放模仿学习
Scaling Imitation Learning in Minecraft
论文作者
论文摘要
模仿学习是在沉浸式环境中学习感觉运动协调的强大技术。我们将模仿学习应用于在我的Minecraft环境中实现最新勘探问题的最先进表现。我们报告了突出网络体系结构，损耗函数和数据增强影响的实验。我们方法的早期版本在2019年Neurips的矿机竞争中排名第二。在这里，我们报告的结果更强，可以用作将来的竞争参赛作品和相关研究的起点。我们的代码可从https://github.com/amiranas/minerl_imitation_learning获得。
Imitation learning is a powerful family of techniques for learning sensorimotor coordination in immersive environments. We apply imitation learning to attain state-of-the-art performance on hard exploration problems in the Minecraft environment. We report experiments that highlight the influence of network architecture, loss function, and data augmentation. An early version of our approach reached second place in the MineRL competition at NeurIPS 2019. Here we report stronger results that can be used as a starting point for future competition entries and related research. Our code is available at https://github.com/amiranas/minerl_imitation_learning.
