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Following this, Das et al. [54] also presented a modular approach to further enhance this process by teaching the agent to break the master policy into subgoals that are also interpretable by humans and execute them to answer the question. This proved to increase the success rate.

Interactive Question Answering (IQA) is closely related to the Embodied version of it. The only main issue is that question is designed in a way that the agent must interact with the environment to find the answer. For example, it has to open the refrigerator or pick up something from the cabinet and then plan for a series of actions conditioned on the question [55].

Multi‐agent systems (MAS) is another interesting line of development. The default standpoint of AI has a strong focus on individual agents. MAS research that has its origins in the field of biology tries to change this and studies the emergence of behaviors in groups of agents or swarms instead [56, 57].