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In this section, we try to categorize a broad range of research that has been done under the field of embodied AI. Due to the huge diversity, each section will necessarily be abstract and selective and reflect the authors' personal opinion.

Machine and human communication has always been a topic of interest. As time goes on, more and more aspects of our lives are controlled by AIs, and hence it is crucial to have ways to talk with them. This is a must for giving new instructions to them or receiving an answer from them, and since we are talking about general day‐to‐day machines, we desire this interface to be higher level than programming languages and closer to spoken language. To achieve this, machines must be capable of relating language to actions and the world. Language grounding is the field that tries to tackle this and map natural language instructions to robot behavior.

Hermann et al.'s study shows that this can be achieved by rewarding an agent upon successful execution of written instructions in a 3D environment with a combination of unsupervised learning and reinforcement learning [29]. They also argue that their agent can generalize well after training and can interpret new unseen instructions and operate in unfamiliar situations.