Nowak M A, Plotkin J B, Krakauer D C
Institute for Advanced Study, Olden Lane, Princeton, NJ, 08540, USA.
J Theor Biol. 1999 Sep 21;200(2):147-62. doi: 10.1006/jtbi.1999.0981.
We explore how evolutionary game dynamics have to be modified to accomodate a mathematical framework for the evolution of language. In particular, we are interested in the evolution of vocabulary, that is associations between signals and objects. We assume that successful communication contributes to biological fitness: individuals who communicate well leave more offspring. Children inherit from their parents a strategy for language learning (a language acquisition device). We consider three mechanisms whereby language is passed from one generation to the next: (i) parental learning: children learn the language of their parents; (ii) role model learning: children learn the language of individuals with a high payoff; and (iii) random learning: children learn the language of randomly chosen individuals. We show that parental and role model learning outperform random learning. Then we introduce mistakes in language learning and study how this process changes language over time. Mistakes increase the overall efficacy of parental and role model learning: in a world with errors evolutionary adaptation is more efficient. Our model also provides a simple explanation why homonomy is common while synonymy is rare.
我们探讨了进化博弈动力学如何必须被修改，以适应语言进化的数学框架。特别地，我们关注词汇的进化，即信号与对象之间的关联。我们假设成功的交流有助于生物适应性：交流良好的个体留下更多后代。儿童从父母那里继承语言学习策略（一种语言习得机制）。我们考虑语言从一代传递到下一代的三种机制：（i）父母学习：儿童学习父母的语言；（ii）榜样学习：儿童学习具有高收益个体的语言；以及（iii）随机学习：儿童学习随机选择个体的语言。我们表明，父母学习和榜样学习优于随机学习。然后我们在语言学习中引入错误，并研究这个过程如何随时间改变语言。错误提高了父母学习和榜样学习的整体效率：在一个存在错误的世界中，进化适应更有效。我们的模型还为同音异义词常见而异义词罕见提供了一个简单解释。
