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Contributors:
  1. Shane Steinert-Threlkeld
  2. Jakub Szymanik

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Category: Project

Description: This project explores the evolution of the universal of monotonicity in the semantics of quantifiers with the help of a computational model. It combines the iterated learning paradigm with neural networks as a model of learning. This project contains the data that we present in the paper. The code for reproducing the results is available at https://github.com/thelogicalgrammar/NeuralNetIteratedQuantifiers.

Has supplemental materials for The emergence of monotone quantifiers via iterated learning on PsyArXiv

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