Language Evolution and Computation Bibliography

Can we communicate across the barrier of languages, with images instead of sounds? The scientists behind the color game will document the evolution of a new kind of language, a language beyond words. They will explore the way that new symbols emerge, acquire a meaning, or change their meaning, over time and across space. Will the color game give birth to different dialects, languages that only some people can understand but not others? Will the images of the color game evolve in the same way that words for colour evolved through human history? These are some of the questions that the creators of the Color Game hope to answer.

ColorSims 2.0 is an extension to the existing python package ColorSims [14] which includes notable updates and additions to the original package. ColorSims/ColorSims 2.0 is a python package for simulating the cultural evolution of linguistic color naming conventions. The package can be initialized with random agents or population data (i.e. World Color Survey). The components of the package are modular, allowing the user to vary them independently. Implemented parameters include: dimensions of the color space, population size, social network structure, and agent learning mechanisms (i.e. reinforcement learning, updating) within the evolutionary dynamics in addition to on-board utilities for storing data and visualizing simulation results.

We present a new open source software tool called BEASTling, designed to simplify the preparation of Bayesian phylogenetic analyses of linguistic data using the BEAST 2 platform. BEASTling transforms comparatively short and human-readable configuration files into the XML files used by BEAST to specify analyses. By taking advantage of Creative Commons-licensed data from the Glottolog language catalog, BEASTling allows the user to conveniently filter datasets using names for recognised language families, to impose monophyly constraints so that inferred language trees are backward compatible with Glottolog classifications, or to assign geographic location data to languages for phylogeographic analyses. Support for the emerging cross-linguistic linked data format (CLDF) permits easy incorporation of data published in cross-linguistic linked databases into analyses. BEASTling is intended to make the power of Bayesian analysis more accessible to historical linguists without strong programming backgrounds, in the hopes of encouraging communication and collaboration between those developing computational models of language evolution (who are typically not linguists) and relevant domain experts.