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Evolutionary neural network model of universal grammar

机译:通用语法的进化神经网络模型

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摘要

Acquisition and performance of languages or grammar are the typical intellectual activities of human beings, and various models of these processes using neural networks have been proposed. These activities, however, are considered not to be learned completely anew in each individual, but also to have been acquired over the long evolutionary history of human beings. The universal grammar is assumed to be a comprehensive knowledge of grammar that was acquired and hardwired in the brain during human evolution. By employing neuroevolution, we illustrate how the universal grammar might have evolved in the neural network using a genetic algorithm.
机译:语言或语法的习得和表演是人类的典型智力活动,并且已经提出了使用神经网络的这些过程的各种模型。然而,这些活动被认为不是每个人都重新学习的,而是在人类漫长的进化历史中习得的。通用语法被认为是在人类进化过程中在大脑中获得并硬连线的语法的综合知识。通过使用神经进化,我们说明了使用遗传算法在神经网络中通用语法可能是如何演化的。

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