It has been argued that semantic systems reflect pressure for efficiency, and a current debate concerns the cultural evolutionary process that produces this pattern. We consider efficiency as instantiated in the Information Bottleneck (IB) principle, and a model of cultural evolution that combines iterated learning and communication. We show that this model, instantiated in neural networks, converges to color naming systems that are efficient in the IB sense and similar to human color naming systems. We also show that iterated learning alone, and communication alone, do not yield the same outcome as clearly.

翻译：已有研究认为语义系统反映了效率压力，当前的一个争议点是产生这种模式的文化演化过程。我们将效率视为信息瓶颈（Information Bottleneck, IB）原则的具体体现，并构建了一个结合迭代学习与交流的文化演化模型。研究表明，在神经网络中实现的该模型，会收敛到符合IB原则、且与人类颜色命名系统相似的高效颜色命名系统。同时我们也发现，仅凭迭代学习或仅凭交流，均难以如此明确地产生相同结果。