The MineRL 2021 Diamond Competition aims to foster the development of algorithms which can efficiently leverage human demonstrations to drastical

AIcrowd | NeurIPS 2021: MineRL Diamond Competition | Challenges

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2021-06-09 13:30:05

The MineRL 2021 Diamond Competition aims to foster the development of algorithms which can efficiently leverage human demonstrations to drastically reduce the number of samples needed to solve complex, hierarchical, and sparse environments.

To that end, participants will compete to develop systems that can obtain a diamond in Minecraft from raw pixels using only 8,000,000 samples from the MineRL simulator and 4 days of training on a single GPU machine. Participants will be provided the MineRL-v0 dataset (website, paper), a large-scale collection of over 60 million frames of human demonstrations, enabling them to utilize expert trajectories to minimize their algorithm’s interactions with the Minecraft simulator.

The major difference is the inclusion of two tracks: Intro and Research. The Research track follows the setup of the MineRL 2020 competition, where agents are retrained using submitted code, must use the obfuscated environments, and cannot contain hardcoding. The Intro track loosens these rules by using the non-obfuscated environments and allowing hardcoded behaviour.

The task of the competition is solving the MineRLObtainDiamond-v0 environment (or MineRLObtainDiamondVectorObf-v0 for Research track). In this environment, the agent begins in a random starting location without any items, and is tasked with obtaining a diamond. This task can only be accomplished by navigating the complex item hierarchy of Minecraft.