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Agent-based models for the emergence and evolution of grammar

机译:基于代理的语法的出现和发展模型

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摘要

Human languages are extraordinarily complex adaptive systems. They feature intricate hierarchical sound structures, are able to express elaborate meanings and use sophisticated syntactic and semantic structures to relate sound to meaning. What are the cognitive mechanisms that speakers and listeners need to create and sustain such a remarkable system? What is the collective evolutionary dynamics that allows a language to self-organize, become more complex and adapt to changing challenges in expressive power? This paper focuses on grammar. It presents a basic cycle observed in the historical language record, whereby meanings move from lexical to syntactic and then to a morphological mode of expression before returning to a lexical mode, and discusses how we can discover and validate mechanisms that can cause these shifts using agent-based models.
机译:人类语言是极其复杂的自适应系统。它们具有复杂的分层声音结构,能够表达详尽的含义,并使用复杂的句法和语义结构将声音与含义相关联。演讲者和听众创建和维持如此出色的系统需要哪些认知机制?集体进化的动力是什么,使语言能够自我组织,变得更加复杂并适应表达能力不断变化的挑战?本文主要关注语法。它提供了在历史语言记录中观察到的一个基本周期,即意义从词法变为句法,然后又转变为形态表达模式,然后再返回到词法模式,并讨论了如何使用智能体发现和验证可能导致这些转变的机制基于模型。

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