Acquisition and Evolution of quasi-regular languages: Two puzzles for the price of one
Matthew Roberts, Luca Onnis, & Nick Chater
Abstract
The quasi-productivity of natural languages appears to pose two difficult problems for language
research. Firstly, why do irregularities in natural language not disappear over time, leaving
languages completely regular (a transmission problem), and secondly, how did such irregularity
arise in the first place (an emergence problem)? To address the transmission problem, we present an
artificial, simplicity-based learner capable of acquiring quasi-regular structures.
In doing so, we present an explicitly psychological model of a famously problematic aspect of
language acquisition known as Baker's Paradox. We present several simulations of an Iterated Learning
Model (ILM) illustrating the emergence and stability of quasi-regular irregularities using a
rudimentary language. These simulations offer a possible resolution to the emergence problem.
Other possible resolutions are discussed.
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