Recent work (Xu et al., 2020) has suggested that numeral systems in different languages are shaped by a functional need for efficient communication in an information-theoretic sense. Here we take a learning-theoretic approach and show how efficient communication emerges via reinforcement learning. In our framework, two artificial agents play a Lewis signaling game where the goal is to convey a numeral concept. The agents gradually learn to communicate using reinforcement learning and the resulting numeral systems are shown to be efficient in the information-theoretic framework of Regier et al. (2015); Gibson et al. (2017). They are also shown to be similar to human numeral systems of same type. Our results thus provide a mechanistic explanation via reinforcement learning of the recent results in Xu et al. (2020) and can potentially be generalized to other semantic domains.

翻译：近期研究（Xu et al., 2020）表明，不同语言中的数字系统在信息论意义上受到高效沟通功能需求的塑造。本文采用学习理论视角，展示如何通过强化学习实现高效沟通。在我们的框架中，两个智能体进行刘易斯信号博弈，目标为传递数字概念。智能体通过强化学习逐步学会沟通，所得数字系统在Regier等人（2015）与Gibson等人（2017）的信息论框架中被证明是高效的，且与同类型人类数字系统具有相似性。因此，我们的结果为Xu等人（2020）的最新发现提供了基于强化学习的机制性解释，并有望推广至其他语义领域。