论文标题
保持简单：在语言科学中适应和学习的原始原则的实施和表现
Keeping it simple: Implementation and performance of the proto-principle of adaptation and learning in the language sciences
论文作者
论文摘要
在本文中，我们介绍了widrow-hoff规则及其在语言数据中的应用。在将历史上的规则背景下，并将其置于神经启发的人工学习模型链中，我们解释了其原理和实施式考虑因素。我们使用许多案例研究说明了如何为一系列语言现象的计算模拟提供意外的机会，从而使从新颖的角度解决旧问题成为可能。
In this paper we present the Widrow-Hoff rule and its applications to language data. After contextualizing the rule historically and placing it in the chain of neurally inspired artificial learning models, we explain its rationale and implementational considerations. Using a number of case studies we illustrate how the Widrow-Hoff rule offers unexpected opportunities for the computational simulation of a range of language phenomena that make it possible to approach old problems from a novel perspective.
