One contribution of 13 to a theme issue 'The major synthetic evolutionary transitions'.Subject Areas: computational biology, evolution Keywords: language evolution, grammaticalization, emergence of grammar, fluid construction grammar, agent-based models, major transitions in evolution Author for correspondence: Luc Steels e-mail: steels@arti.vub.ac.be Agent-based models for the emergence and evolution of grammar Luc Steels ICREA, IBE-Universitat Pompeu Fabra and CSIC, 08003 Barcelona, Spain LS, 0000-0001-9134-3663Human 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.This article is part of the themed issue 'The major synthetic evolutionary transitions'.
Stages in language evolutionA human language is a remarkable, highly complex communication system. The capacity for language, the so-called language-ready brain [1], uniquely emerged in the hominin species, perhaps being in place as far back as half a million years ago [2]. Since then, languages have been born, and existing languages have kept changing, diversifying and dying. How can we develop a scientific understanding of the emergence and continuous cultural evolution of such a highly complex system? Analogous to a successful strategy in evolutionary biology [3], we could postulate different stages for the emergence of language in a population with language-ready brains, based on criteria related to the complexity of the meanings that can be conveyed and the complexity of the structures and linguistic forms available to express them.To study how complexity at each stage arises and what is required to see transitions between stages, we could adopt the synthetic method, which is being used increasingly in many scientific fields, particularly biology [4], but also fields studying culturally evolving systems, such as sociology [5] or archaeology [6]. This method suggests that we should build operational models that generate analogous behaviours to those observed in the natural system we want to understand, similar to the way an aeroplane can be said to exhibit a similar capacity to fly as birds and hence informs us about what it takes to fly. In the case of language, the operational models take the form of a population of artificial agents which are initialized with a set of ...