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arXiv · 2305.11962

Spatial community structure impedes language amalgamation in a population-based iterated learning model

George Sains·Conor Houghton·Seth Bullock
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Abstract

The iterated learning model is an agent-based model of language evolution notable for demonstrating the emergence of compositional language. In its original form, it modelled language evolution along a single chain of teacher-pupil interactions; here we modify the model to allow more complex patterns of communication within a population and use the extended model to quantify the effect of within-community and between-community communication frequency on language development. We find that a small amount of between-community communication can lead to population-wide language convergence but that this global language amalgamation is more difficult to achieve when communities are spatially embedded.

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George Sains, Conor Houghton, Seth Bullock. 2023-05-19. Spatial community structure impedes language amalgamation in a population-based iterated learning model. https://doi.org/10.1162/isal_a_00657

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