Language evolution is shaped by the structure of the world: An iterated learning analysis

Abstract

Human languages vary in many ways, but also show strik-ing cross-linguistic universals. Why do these universals ex-ist? Recent theoretical results demonstrate that Bayesian learn-ers transmitting language to each other through iterated learn-ing will converge on a distribution of languages that depends only on their prior biases about language and the quantity of data transmitted at each point; the structure of the world being communicated about plays no role (Griffiths & Kalish, 2005, 2007). We revisit these findings and show that when certain as-sumptions about the independence of languages and the world are abandoned, learners will converge to languages that depend on the structure of the world as well as their prior biases. These theoretical results are supported with a series of experiments showing that when human learners acquire language through iterated learning, the ultimate structure of those languages is shaped by the structure of the meanings to be communicated.

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