The iterated classification game (ICG) combines the classification game with the iterated learning model (ILM) to create a more realistic model of the cultural transmission of language through generations. It includes both learning from parents and learning from peers. Further, it eliminates some of the chief criticisms of the ILM: that it does not study grounded languages, that it does not include peer learning, and that it builds in a bias for compositional languages. We show that, over the span of a few generations, a stable linguistic system emerges that can be acquired very quickly by each generation, is compositional, and helps the agents to solve the classification problem with which they are faced. The ICG also leads to a different interpretation of the language acquisition process. It suggests that the role of parents is to initialize the linguistic system of the child in such a way that subsequent interaction with peers results in rapid convergence to the correct language.

中文翻译：

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迭代分类博弈：语言文化传播的新模型

迭代分类游戏 (ICG) 将分类游戏与迭代学习模型 (ILM) 相结合，以创建更真实的语言代际文化传播模型。它包括向父母学习和向同龄人学习。此外，它消除了对 ILM 的一些主要批评：它不研究基础语言，不包括同伴学习，以及它对组合语言的偏见。我们表明，在几代人的跨度内，出现了一个稳定的语言系统，每一代人都可以很快获得它，它是组合式的，并帮助代理解决他们面临的分类问题。ICG 还导致对语言习得过程的不同解释。