On Clustering Trend in Language Evolution Based on Dynamical Behaviors of Multi-Agent Model

TL;DR

This paper presents a multi-agent lattice model to simulate language evolution, revealing that languages tend to cluster into distinct groups over time, providing insights into the dynamics of language change.

Contribution

It introduces a novel multi-agent lattice model to study language evolution, highlighting the clustering phenomenon and offering a new computational approach to understanding language dynamics.

Findings

Languages converge into several clusters during evolution

The model demonstrates the influence of local interactions on language change

Clustering behavior provides insights into language evolution patterns

Abstract

Computer model has been extensively adopted to overcome the time limitation of language evolution by transforming language theory into physical modeling mechanism, which helps to explore the general laws of the evolution. In this paper, a multi-agent model is designed to simulate the evolution process of language in human settlements, with the network topology being lattice. The language of each node in the lattice will evolve gradually under the influence of its own fixed evolutionary direction and neighbors. According to the computational experiment results, it is discovered that the state points of languages always converge into several clusters during evolution process, which gives us an insight into language evolution.