Simplicity and informativeness in semantic category systems

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Description: This repository includes Python code for running a Bayesian iterated learning model of the emergence of semantic categories (plus the raw data that we generated from this model), and code for running online experiments that test the predictions of the model (plus the participant data we collected). Various other Python and R scripts are also included for replicating the analysis. All Python code in this repo was written for Python 3 and much of it requires NumPy, SciPy, and matplotlib to be installed. Note that the code and data make reference to two experiments, but the final paper only reports Experiment 2 (the iterated learning experiment). Details about Experiment 1 (a category learning experiment) can be found in my thesis: https://joncarr.net/s/carr-2019-phd-thesis.pdf (Chapter 3)

License: CC-By Attribution 4.0 International

Has supplemental materials for Simplicity and informativeness in semantic category systems on PsyArXiv

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