Language may help AI navigate new environments

In a new study published this week on the preprint server Arxiv.org, Both it and several baseline models will soon be available on GitHub. One of the most powerful techniques in machine learning -- reinforcement learning, which entails spurring software agents toward goals via rewards -- is also one of the most flawed. It's sample inefficient, meaning it requires a large number of compute cycles to complete, and without additional data to cover variations, it adapts poorly to environments that differ from the training environment. It's theorized that prior knowledge of tasks through structured language could be combined with reinforcement learning to mitigate its shortcomings, and BabyAI was designed to put this theory to the test.