  Human intelligence has the remarkable ability to adapt to new tasks and
environments quickly. Starting from a very young age, humans acquire new skills
and learn how to solve new tasks either by imitating the behavior of others or
by following provided natural language instructions. To facilitate research in
this direction, we propose IGLU: Interactive Grounded Language Understanding in
a Collaborative Environment. The primary goal of the competition is to approach
the problem of how to develop interactive embodied agents that learn to solve a
task while provided with grounded natural language instructions in a
collaborative environment. Understanding the complexity of the challenge, we
split it into sub-tasks to make it feasible for participants.
  This research challenge is naturally related, but not limited, to two fields
of study that are highly relevant to the NeurIPS community: Natural Language
Understanding and Generation (NLU/G) and Reinforcement Learning (RL).
Therefore, the suggested challenge can bring two communities together to
approach one of the crucial challenges in AI. Another critical aspect of the
challenge is the dedication to perform a human-in-the-loop evaluation as a
final evaluation for the agents developed by contestants.
