A Social Approach to Rule Dynamics Using an Agent-Based Model

Authored by Christine Cuskley, Vittorio Loreto, Simon Kirby

Date Published: 2018

DOI: 10.1111/tops.12327

Sponsors: No sponsors listed

Platforms: C++

Model Documentation: Flow charts

Model Code URLs: https://github.com/CCuskley/RuleEmergence

Abstract

A well-trod debate at the nexus of cognitive science and linguistics, the so-called past tense debate, has examined how rules and exceptions are individually acquired (McClelland \& Patterson, ; Pinker \& Ullman, ). However, this debate focuses primarily on individual mechanisms in learning, saying little about how rules and exceptions function from a sociolinguistic perspective. To remedy this, we use agent-based models to examine how rules and exceptions function across populations. We expand on earlier work by considering how repeated interaction and cultural transmission across speakers affects the dynamics of rules and exceptions in language, measuring linguistic outcomes within a social system rather than focusing individual learning outcomes. We consider how population turnover and growth effect linguistic rule dynamics in large and small populations, showing that this method has considerable potential particularly in probing the mechanisms underlying the linguistic niche hypothesis (Lupyan \& Dale, ). Cuskley, Loreto \& Kirby (2018) explore how the diversity of social groups influences the linguistic system. Using agent-based modelling for simulating language evolution in a concentrated time frame, they suggest that the morphology of languages (e.g. the plural -s or past tense -ed in English) used in larger groups including more non-native speakers is less complex.

Tags

Agent-based modeling regularity Rules Population size Linguistics Population growth Languages