Spontaneous evolution of linguistic structure-an iterated learning model of the emergence of regularity and irregularity

TLDR

The study presents a computational model of linguistic behavior transmission over time. The iterated learning model simulates language transmission without biological evolution, natural selection, or communicative success metrics. The model shows that even without selection pressures, linguistic behavior evolves from an unstructured protolanguage into a fully compositional syntactic system, producing realistic string‑length distributions and stable irregularities.

Abstract

A computationally implemented model of the transmission of linguistic behavior over time is presented. In this iterated learning model (ILM), there is no biological evolution, natural selection, nor any measurement of the success of the agents at communicating (except for results-gathering purposes). Nevertheless, counter to intuition, significant evolution of linguistic behavior is observed. From an initially unstructured communication system (a protolanguage), a fully compositional syntactic meaning-string mapping emerges. Furthermore, given a nonuniform frequency distribution over a meaning space and a production mechanism that prefers short strings, a realistic distribution of string lengths and patterns of stable irregularity emerges, suggesting that the ILM is a good model for the evolution of some of the fundamental features of human language.