  The BabyAI platform is designed to measure the sample efficiency of training
an agent to follow grounded-language instructions. BabyAI 1.0 presents baseline
results of an agent trained by deep imitation or reinforcement learning. BabyAI
1.1 improves the agent's architecture in three minor ways. This increases
reinforcement learning sample efficiency by up to 3 times and improves
imitation learning performance on the hardest level from 77 % to 90.4 %. We
hope that these improvements increase the computational efficiency of BabyAI
experiments and help users design better agents.
