Komarova N L, Nowak M A
Institute for Advanced Study, Einstein Drive, Princeton, NJ 08540, USA.
Bull Math Biol. 2001 May;63(3):451-84. doi: 10.1006/bulm.2000.0222.
The lexical matrix is an integral part of the human language system. It provides the link between word form and word meaning. A simple lexical matrix is also at the center of any animal communication system, where it defines the associations between form and meaning of animal signals. We study the evolution and population dynamics of the lexical matrix. We assume that children learn the lexical matrix of their parents. This learning process is subject to mistakes: (i) children may not acquire all lexical items of their parents (incomplete learning); and (ii) children might acquire associations between word forms and word meanings that differ from their parents' lexical items (incorrect learning). We derive an analytic framework that deals with incomplete learning. We calculate the maximum error rate that is compatible with a population maintaining a coherent lexical matrix of a given size. We calculate the equilibrium distribution of the number of lexical items known to individuals. Our analytic investigations are supplemented by numerical simulations that describe both incomplete and incorrect learning, and other extensions.
词汇矩阵是人类语言系统不可或缺的一部分。它提供了词形与词义之间的联系。一个简单的词汇矩阵也是任何动物交流系统的核心,在动物交流系统中,它定义了动物信号的形式与意义之间的关联。我们研究词汇矩阵的进化和种群动态。我们假设儿童学习其父母的词汇矩阵。这个学习过程容易出错:(i)儿童可能没有习得其父母的所有词汇项(不完全学习);以及(ii)儿童可能习得与父母词汇项不同的词形与词义之间的关联(错误学习)。我们推导了一个处理不完全学习的分析框架。我们计算了与维持给定大小的连贯词汇矩阵的种群兼容的最大错误率。我们计算了个体所知词汇项数量的平衡分布。我们的分析研究辅以描述不完全学习和错误学习以及其他扩展情况的数值模拟。