Sequence Memory Constraints Give Rise to Language-Like Structure through Iterated Learning.

Sequence Memory Constraints Give Rise to Language-Like Structure through Iterated Learning.

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Human language is composed of sequences of reusable elements.The origins of the sequential structure of language is a hotly debated topic in evolutionary linguistics.In this paper, we show that sets of sequences with language-like statistical properties can emerge from a mozelle riesling process of cultural evolution under pressure from chunk-based memory constraints.We employ a novel experimental task that is non-linguistic and non-communicative in nature, in which participants are trained on and later asked to recall a set of sequences one-by-one.

Recalled sequences from one participant become training data for the next participant.In this way, farmhouse magnolia wreath we simulate cultural evolution in the laboratory.Our results show a cumulative increase in structure, and by comparing this structure to data from existing linguistic corpora, we demonstrate a close parallel between the sets of sequences that emerge in our experiment and those seen in natural language.