To develop computational agents that better communicate using their own emergent language, we endow the agents with an ability to focus their attention on particular concepts in the environment. Humans often understand an object or scene as a composite of concepts and those concepts are further mapped onto words. We implement this intuition as cross-modal attention mechanisms in Speaker and Listener agents in a referential game and show attention leads to more compositional and interpretable emergent language. We also demonstrate how attention aids in understanding the learned communication protocol by investigating the attention weights associated with each message symbol and the alignment of attention weights between Speaker and Listener agents. Overall, our results suggest that attention is a promising mechanism for developing more human-like emergent language.

翻译：为了开发能够更好利用自身涌现语言进行交流的计算智能体，我们赋予智能体将注意力聚焦于环境中特定概念的能力。人类通常将物体或场景理解为多个概念的组合，而这些概念又进一步映射到词汇上。我们通过在指代游戏中的说话者和听众智能体中实现跨模态注意力机制来实施这一直觉，并证明注意力能够产生更具组合性和可解释性的涌现语言。此外，我们还通过研究每个消息符号对应的注意力权重，以及说话者和听众智能体之间注意力权重的对齐，展示了注意力如何帮助理解习得的通信协议。总体而言，我们的结果表明注意力是一种开发更类人涌现语言的有效机制。