Agent-based models for the emergence and evolution of grammar

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Abstract

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.

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APA

Steels, L. (2016). Agent-based models for the emergence and evolution of grammar. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1701). https://doi.org/10.1098/rstb.2015.0447

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